📄 AI4Research: A Survey of Artificial Intelligence for Scientific Research

Paper · 2025 · Qiguang Chen, Mingda Yang, Libo Qin et al.

Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.

🏛️ Institutions

🎓University of Illinois Urbana-ChampaignUrbana · United States184 works · 69,372 citations🎓Fudan UniversityShanghai · China167 works · 20,987 citations🎓Princeton UniversityPrinceton · United States90 works · 39,109 citations🎓Harbin Institute of TechnologyHarbin · China158 works · 28,841 citations🎓Chinese University of Hong KongHong Kong · China126 works · 14,073 citations🎓University of Hong KongPok Fu Lam · China89 works · 11,774 citations🎓Central South UniversityChangsha · China15 works · 582 citations

🧭 Fields, topics and concepts

Cite

Cite as Qiguang Chen, Mingda Yang, Libo Qin, Jinhao Liu, Zheng Yan, Jiannan Guan, Dengyun Peng, Yiyan Ji, Hanjing Li, Mengkang Hu, Yimeng Zhang, Yihao Liang, Yuhang Zhou, Jiaqi Wang, Zhi Chen and Wanxiang Che. 2025. AI4Research: A Survey of Artificial Intelligence for Scientific Research. arXiv:2507.01903.

The paper itself, not this page. BibTeX from the library's record of the work. DOI 10.48550/arxiv.2507.01903 · arXiv 2507.01903

@misc{chen2025ai4research,
  title = {{AI4Research: A Survey of Artificial Intelligence for Scientific Research}},
  author = {Qiguang Chen, Mingda Yang, Libo Qin, Jinhao Liu, Zheng Yan, Jiannan Guan, Dengyun Peng, Yiyan Ji, Hanjing Li, Mengkang Hu, Yimeng Zhang, Yihao Liang, Yuhang Zhou, Jiaqi Wang, Zhi Chen and Wanxiang Che},
  year = {2025},
  doi = {10.48550/arxiv.2507.01903},
  eprint = {2507.01903},
  archivePrefix = {arXiv},
  url = {https://doi.org/10.48550/arxiv.2507.01903}
}

References

960 references, 108 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

1. Marah Abdin, Jyoti Aneja, Harkirat Behl, Sébastien Bubeck, Ronen Eldan, Suriya Gunasekar, Michael Harrison, Russell J Hewett, Mojan Javaheripi, Piero Kauffmann, et al. Phi-4 technical report. arXiv preprint arXiv:2412.08905, 2024.
2. Josh Abramson, Jonas Adler, Jack Dunger, Richard Evans, Tim Green, Alexander Pritzel, Olaf Ronneberger, Lindsay Willmore, Andrew J Ballard, Joshua Bambrick, et al. Accurate structure prediction of biomolecular interactions with alphafold 3. Nature, 630(8016):493–500, May 2024. find
3. Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al. Gpt-4 technical report. arXiv preprint arXiv:2303.08774, 2023.
4. Pierre Achkar, Tim Gollub, and Martin Potthast. Ask, retrieve, summarize: A modular pipeline for scientific literature summarization. arXiv preprint arXiv:2505.16349, 2025. — [arXiv:2505.16349](https://arxiv.org/abs/2505.16349) find
5. Steven Adriaensen, Herilalaina Rakotoarison, Samuel Müller, and Frank Hutter. Efficient bayesian learning curve extrapolation using prior-data fitted networks. Advances in Neural Information Processing Systems, 36:19858–19886, Dec 2023. find
6. Tejumade Afonja, Ivaxi Sheth, Ruta Binkyte, Waqar Hanif, Thomas Ulas, Matthias Becker, and Mario Fritz. Llm4grn: Discovering causal gene regulatory networks with llms–evaluation through synthetic data generation. arXiv preprint arXiv:2410.15828, 2024. find
7. Shubham Agarwal, Gaurav Sahu, Abhay Puri, Issam H Laradji, Krishnamurthy DJ Dvijotham, Jason Stanley, Laurent Charlin, and Christopher Pal. Litllm: A toolkit for scientific literature review. arXiv preprint arXiv:2402.01788, 2024. find
8. Shubham Agarwal, Gaurav Sahu, Abhay Puri, Issam H Laradji, Krishnamurthy DJ Dvijotham, Jason Stanley, Laurent Charlin, and Christopher Pal. Llms for literature review: Are we there yet? arXiv preprint arXiv:2412.15249, 2024.
9. Shubham Agarwal, Gaurav Sahu, Abhay Puri, Issam H. Laradji, Krishnamurthy Dj Dvijotham, Jason Stanley, Laurent Charlin, and Christopher Pal. LitLLMs, LLMs for literature review: Are we there yet? Transactions on Machine Learning Research, Apr 2025. ISSN 2835-8856. URL https://openreview.net/forum?i… ↗
10. Ajay Agrawal, John McHale, and Alexander Oettl. Artificial intelligence and scientific discovery: A model of prioritized search. Research Policy, 53(5):104989, Jun 2024. find
11. Melih Agraz, Dincer Goksuluk, Peng Zhang, Bum-Rak Choi, Richard T Clements, Gaurav Choudhary, and George Em Karniadakis. Ml-gap: machine learning-enhanced genomic analysis pipeline using autoencoders and data augmentation. Frontiers in Genetics, 15:1442759, Sep 2024. find
12. Intology AI. Zochi technical report, Mar 2025. URL https://github.com/IntologyAI/Zochi/ blob/main/Zochi_Technical_Report.pdf. Zochi Technical Report. ↗
13. Nurmukhammed Aitymbetov and Dimitrios Zorbas. Autonomous machine learning-based peer reviewer selection system. In Proceedings of the 31st International Conference on Computational Linguistics: System Demonstrations, pages 199–207, Jan 2025. find
14. Andres Algaba, Vincent Holst, Floriano Tori, Melika Mobini, Brecht Verbeken, Sylvia Wenmackers, and Vincent Ginis. How deep do large language models internalize scientific literature and citation practices? arXiv preprint arXiv:2504.02767, 2025. — [arXiv:2504.02767](https://arxiv.org/abs/2504.02767) find
15. Atilla Kaan Alkan, Shashwat Sourav, Maja Jablonska, Simone Astarita, Rishabh Chakrabarty, Nikhil Garuda, Pranav Khetarpal, Maciej Pióro, Dimitrios Tanoglidis, Kartheik G Iyer, et al. A survey on hypothesis generation for scientific discovery in the era of large language models. arXiv preprint arXiv:… — [arXiv:2504.05496](https://arxiv.org/abs/2504.05496) find
16. Enes Altuncu, Jason RC Nurse, Meryem Bagriacik, Sophie Kaleba, Haiyue Yuan, Lisa Bonheme, and Shujun Li. aedfact: Scientific fact-checking made easier via semi-automatic discovery of relevant expert opinions. arXiv preprint arXiv:2305.07796, 2023. — [arXiv:2305.07796](https://arxiv.org/abs/2305.07796) find
17. Carlos Alvarez, Maxwell Bennett, and Lucy Lu Wang. Zero-shot scientific claim verification using llms and citation text. In Proceedings of the Fourth Workshop on Scholarly Document Processing (SDP 2024), pages 269–276, Aug 2024. find
18. Jose M Alvarez, Alejandra Bringas Colmenarejo, Alaa Elobaid, Simone Fabbrizzi, Miriam Fahimi, Antonio Ferrara, Siamak Ghodsi, Carlos Mougan, Ioanna Papageorgiou, Paula Reyero, et al. Policy advice and best practices on bias and fairness in ai. Ethics and Information Technology, 26(2):31, Apr 2024. find
19. Tatsuya Amano, Juan P González-Varo, and William J Sutherland. Languages are still a major barrier to global science. PLoS biology, 14(12):e2000933, Dec 2016. find
20. Tatsuya Amano, Clarissa Rios Rojas, Yap Boum II, Margarita Calvo, and Biswapriya B Misra. Ten tips for overcoming language barriers in science. Nature Human Behaviour, 5(9):1119–1122, Jul 2021. find
21. Barrett R Anderson, Jash Hemant Shah, and Max Kreminski. Homogenization effects of large language models on human creative ideation. In Proceedings of the 16th conference on creativity & cognition, pages 413–425, Jun 2024. find
22. Nicholas H Angello, David M Friday, Changhyun Hwang, Seungjoo Yi, Austin H Cheng, Tiara C Torres-Flores, Edward R Jira, Wesley Wang, Alán Aspuru-Guzik, Martin D Burke, et al. Closed-loop transfer enables artificial intelligence to yield chemical knowledge. Nature, 633(8029):351–358, 2024. find
23. Angelos Angelopoulos, James F Cahoon, and Ron Alterovitz. Transforming science labs into automated factories of discovery. Science Robotics, 9(95):eadm6991, 2024. find
24. AI Anthropic. The claude 3 model family: Opus, sonnet, haiku. Claude-3 Model Card, Mar 2024. find
25. Sören Arlt, Haonan Duan, Felix Li, Sang Michael Xie, Yuhuai Wu, and Mario Krenn. Meta-designing quantum experiments with language models. arXiv preprint arXiv:2406.02470, 2024. — [arXiv:2406.02470](https://arxiv.org/abs/2406.02470) find
26. Akari Asai, Jacqueline He, Rulin Shao, Weijia Shi, Amanpreet Singh, Joseph Chee Chang, Kyle Lo, Luca Soldaini, Sergey Feldman, Mike D’arcy, et al. Openscholar: Synthesizing scientific literature with retrieval-augmented lms. arXiv preprint arXiv:2411.14199, 2024. find
27. Joshua Ashkinaze, Julia Mendelsohn, Li Qiwei, Ceren Budak, and Eric Gilbert. How ai ideas affect the creativity, diversity, and evolution of human ideas: evidence from a large, dynamic experiment. arXiv preprint arXiv:2401.13481, 2024. — [arXiv:2401.13481](https://arxiv.org/abs/2401.13481) find
28. Shir Ashury-Tahan, Yifan Mai, Ariel Gera, Yotam Perlitz, Asaf Yehudai, Elron Bandel, Leshem Choshen, Eyal Shnarch, Percy Liang, Michal Shmueli-Scheuer, et al. The mighty torr: A benchmark for table reasoning and robustness. arXiv preprint arXiv:2502.19412, 2025. find
29. Assafelovic. gpt-researcher, May 2023. gpt-researcher. gpt-researcher. URL https://github.com/assafelovic/ ↗
30. Pepa Atanasova. Generating fact checking explanations. In Accountable and Explainable Methods for Complex Reasoning over Text, pages 83–103. Springer, Apr 2024. find
31. Steven Au, Cameron J Dimacali, Ojasmitha Pedirappagari, Namyong Park, Franck Dernoncourt, Yu Wang, Nikos Kanakaris, Hanieh Deilamsalehy, Ryan A Rossi, and Nesreen K Ahmed. Personalized graph-based retrieval for large language models. arXiv preprint arXiv:2501.02157, 2025. find
32. Sören Auer, Dante AC Barone, Cassiano Bartz, Eduardo G Cortes, Mohamad Yaser Jaradeh, Oliver Karras, Manolis Koubarakis, Dmitry Mouromtsev, Dmitrii Pliukhin, Daniil Radyush, et al. The sciqa scientific question answering benchmark for scholarly knowledge. Scientific Reports, 13(1):7240, May 2023. find
33. Axios. Self-driving labs are the new ai asset. Axios, Aug 2024. URL https://www.axios.com/ 2024/08/09/ai-self-driving-science-labs-research. ↗
34. Shingo Ayabe, Takuto Otomo, Hiroshi Kera, and Kazuhiko Kawamoto. Robustness evaluation of offline reinforcement learning for robot control against action perturbations. arXiv preprint arXiv:2412.18781, 2024. — [arXiv:2412.18781](https://arxiv.org/abs/2412.18781) find
35. Ibrahim Al Azher, Miftahul Jannat Mokarrama, Zhishuai Guo, Sagnik Ray Choudhury, and Hamed Alhoori. Futuregen: Llm-rag approach to generate the future work of scientific article. arXiv preprint arXiv:2503.16561, 2025. — [arXiv:2503.16561](https://arxiv.org/abs/2503.16561) find
36. Jinheon Baek, Sujay Kumar Jauhar, Silviu Cucerzan, and Sung Ju Hwang. Researchagent: Iterative research idea generation over scientific literature with large language models. arXiv preprint arXiv:2404.07738, 2024.
37. Xiaomei Bai, Mengyang Wang, Ivan Lee, Zhuo Yang, Xiangjie Kong, and Feng Xia. Scientific paper recommendation: A survey. Ieee Access, 7:9324–9339, Jan 2019. find
38. Honglin Bao, Siyang Wu, Jiwoong Choi, Yingrong Mao, and James A Evans. Language models surface the unwritten code of science and society. arXiv preprint arXiv:2505.18942, 2025. — [arXiv:2505.18942](https://arxiv.org/abs/2505.18942) find
39. Zhijie Bao, Qingyun Liu, Ying Guo, Zhengqiang Ye, Jun Shen, Shirong Xie, Jiajie Peng, Xuanjing Huang, and Zhongyu Wei. Piors: Personalized intelligent outpatient reception based on large language model with multi-agents medical scenario simulation. arXiv preprint arXiv:2411.13902, 2024. — [arXiv:2411.13902](https://arxiv.org/abs/2411.13902) find
40. Mitra Baratchi, Can Wang, Steffen Limmer, Jan N van Rijn, Holger Hoos, Thomas Bäck, and Markus Olhofer. Automated machine learning: past, present and future. Artificial intelligence review, 57(5): 122, Apr 2024. find
41. Gregory Barber. Google deepmind’s ai dreamed up 380,000 new materials. the next challenge is making them. WIRED, Nov 2023. URL https://www.wired.com/story/ an-ai-dreamed-up-380000-new-materials-the-next-challenge-is-making-them/. ↗
42. Rafael Barbudo, Sebastián Ventura, and José Raúl Romero. Eight years of automl: categorisation, review and trends. Knowledge and Information Systems, 65(12):5097–5149, Aug 2023. find
43. Kristian G Barman, Sascha Caron, Emily Sullivan, Henk W de Regt, Roberto Ruiz de Austri, Mieke Boon, Michael Färber, Stefan Fröse, Faegheh Hasibi, Andreas Ipp, et al. Large physics models: Towards a collaborative approach with large language models and foundation models. arXiv preprint arXiv:2501.05… — [arXiv:2501.05382](https://arxiv.org/abs/2501.05382) find
44. Annabel R Basford, Aaron H Bernardino, Paula CP Teeuwen, Benjamin D Egleston, Joshua Humphreys, Kim E Jelfs, Jonathan R Nitschke, Imogen A Riddell, and Rebecca L Greenaway. Development of an automated workflow for screening the assembly and host–guest behavior of metal-organic cages towards accelera… find
45. Setio Basuki and Masatoshi Tsuchiya. The quality assist: A technology-assisted peer review based on citation functions to predict the paper quality. IEEE Access, 10:126815–126831, Dec 2022. find
46. Bruno C Batista, SV Amrutha, Jie Yan, Beni B Dangi, and Oliver Steinbock. High-throughput robotic collection, imaging, and machine learning analysis of salt patterns: composition and concentration from dried droplet photos. Digital Discovery, 4(4):1030–1041, Feb 2025. find
47. Peter Battaglia, Razvan Pascanu, Matthew Lai, Danilo Jimenez Rezende, et al. Interaction networks for learning about objects, relations and physics. Advances in Neural Information Processing Systems, 29, Dec 2016. find
48. Tim Baumgärtner, Ted Briscoe, and Iryna Gurevych. Peerqa: A scientific question answering dataset from peer reviews. In Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), pag… find
49. Atılım Güneş Baydin, Kyle Cranmer, Pablo de Castro Manzano, Christophe Delaere, Denis Derkach, Julien Donini, Tommaso Dorigo, Andrea Giammanco, Jan Kieseler, Lukas Layer, et al. Toward machine learning optimization of experimental design. Nuclear Physics News, 31(1):25–28, Feb 2021. find
50. Adrián Bazaga, Pietro Lio, and Gos Micklem. Unsupervised pretraining for fact verification by language model distillation. arXiv preprint arXiv:2309.16540, 2023. find
51. Adib Bazgir, Yuwen Zhang, et al. Agentichypothesis: A survey on hypothesis generation using llm systems. Towards Agentic AI for Science: Hypothesis Generation, Comprehension, Quantification, and Validation, Mar 2025. find
52. Joeran Beel, Bela Gipp, Stefan Langer, and Corinna Breitinger. Paper recommender systems: a literature survey. International Journal on Digital Libraries, 17(4):305–338, Jul 2016. find
53. Joeran Beel, Min-Yen Kan, and Moritz Baumgart. Evaluating sakana’s ai scientist for autonomous research: Wishful thinking or an emerging reality towards’ artificial research intelligence’(ari)? arXiv preprint arXiv:2502.14297, 2025. find
54. Jonas Belouadi, Anne Lauscher, and Steffen Eger. Automatikz: Text-guided synthesis of scientific vector graphics with tikz. arXiv preprint arXiv:2310.00367, 2023.
55. Jonas Belouadi, Eddy Ilg, Margret Keuper, Hideki Tanaka, Masao Utiyama, Raj Dabre, Steffen Eger, and Simone Paolo Ponzetto. Tikzero: Zero-shot text-guided graphics program synthesis. arXiv preprint arXiv:2503.11509, 2025. — [arXiv:2503.11509](https://arxiv.org/abs/2503.11509) find
56. Iz Beltagy, Kyle Lo, and Arman Cohan. SciBERT: A pretrained language model for scientific text. In Kentaro Inui, Jing Jiang, Vincent Ng, and Xiaojun Wan, editors, Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natu…
57. Leonard Bereska and Efstratios Gavves. Mechanistic interpretability for ai safety–a review. arXiv preprint arXiv:2404.14082, 2024. find
58. Marialena Bevilacqua, Kezia Oketch, Ruiyang Qin, Will Stamey, Xinyuan Zhang, Yi Gan, Kai Yang, and Ahmed Abbasi. When automated assessment meets automated content generation: Examining text quality in the era of gpts. ACM Trans. Inf. Syst., 43(2), January 2025. ISSN 1046-8188. doi: 10.1145/3702639.… — [doi:10.1145/3702639](https://doi.org/10.1145/3702639) find
59. Prabhat Kumar Bharti, Shashi Ranjan, Tirthankar Ghosal, Mayank Agrawal, and Asif Ekbal. Peerassist: leveraging on paper-review interactions to predict peer review decisions. In Towards Open and Trustworthy Digital Societies: 23rd International Conference on Asia-Pacific Digital Libraries, ICADL 2021… find
60. Prabhat Kumar Bharti, Meith Navlakha, Mayank Agarwal, and Asif Ekbal. Politepeer: does peer review hurt? a dataset to gauge politeness intensity in the peer reviews. Language Resources and Evaluation, 58(4):1291–1313, May 2024. find
61. Haiyang Bian, Yixin Chen, Erpai Luo, Xinze Wu, Minsheng Hao, Lei Wei, and Xuegong Zhang. General-purpose pre-trained large cellular models for single-cell transcriptomics. National Science Review, 11 (11):nwae340, Sep 2024. find
62. Junyi Bian, Xiaolei Qin, Wuhe Zou, Mengzuo Huang, Congyi Luo, Ke Zhang, and Weidong Zhang. Helm: Highlighted evidence augmented language model for enhanced table-to-text generation. arXiv preprint arXiv:2311.08896, 2023. — [arXiv:2311.08896](https://arxiv.org/abs/2311.08896) find
63. Thulasi Bikku, Nirmala Rani Narimalla, Keerthi Konda, Anusha Nakkala, Avanti Yarlagadda, and B Sachuthananthan. Generating accurate and engaging research paper titles using nlp techniques. In International Conference on Innovations in Bio-Inspired Computing and Applications, pages 428–437. Springer,… find
64. Marcel Binz and Eric Schulz. Using cognitive psychology to understand gpt-3. Proceedings of the National Academy of Sciences, 120(6), February 2023. ISSN 1091-6490. doi: 10.1073/pnas. 2218523120. URL http://dx.doi.org/10.1073/pnas.2218523120. ↗
65. Marah Blaurock, Marion Büttgen, and Jeroen Schepers. Designing collaborative intelligence systems for employee-ai service co-production. Journal of Service Research, page 10946705241238751, Mar 2024. find
66. Severin Bochem, Eduardo Gonzalez-Sanchez, Yves Bicker, and Gabriele Fadini. Improving generalization of robot locomotion policies via sharpness-aware reinforcement learning. arXiv preprint arXiv:2411.19732, 2024. — [arXiv:2411.19732](https://arxiv.org/abs/2411.19732) find
67. Amber Boehnlein, Markus Diefenthaler, Nobuo Sato, Malachi Schram, Veronique Ziegler, Cristiano Fanelli, Morten Hjorth-Jensen, Tanja Horn, Michelle P Kuchera, Dean Lee, et al. Colloquium: Machine learning in nuclear physics. Reviews of modern physics, 94(3):031003, Sep 2022. find
68. Daniil A Boiko, Robert MacKnight, Ben Kline, and Gabe Gomes. Autonomous chemical research with large language models. Nature, 624(7992):570–578, Dec 2023.
69. Francisco Bolanos, Angelo Salatino, Francesco Osborne, and Enrico Motta. Artificial intelligence for literature reviews: Opportunities and challenges. Artificial Intelligence Review, 57(10):259, Aug 2024. find
70. Valeriia Bolotova, Vladislav Blinov, Falk Scholer, W Bruce Croft, and Mark Sanderson. A non-factoid question-answering taxonomy. In Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 1196–1207, Jul 2022. find
71. Elliot Bolton, Abhinav Venigalla, Michihiro Yasunaga, David Hall, Betty Xiong, Tony Lee, Roxana Daneshjou, Jonathan Frankle, Percy Liang, Michael Carbin, et al. Biomedlm: A 2.7 b parameter language model trained on biomedical text. arXiv preprint arXiv:2403.18421, 2024.
72. Necva Bölücü, Yunus Can Bilge, Dilber Çetintaş, and Zehra Yücel. Modest: A dataset for multi domain scientific title generation. Knowledge-Based Systems, page 113557, Jun 2025. find
73. Jan A Botha, Manaal Faruqui, John Alex, Jason Baldridge, and Dipanjan Das. Learning to split and rephrase from wikipedia edit history. arXiv preprint arXiv:1808.09468, 2018. find
74. Jack Boylan, Shashank Mangla, Dominic Thorn, Demian Gholipour Ghalandari, Parsa Ghaffari, and Chris Hokamp. Kgvalidator: A framework for automatic validation of knowledge graph construction. arXiv preprint arXiv:2404.15923, 2024. — [arXiv:2404.15923](https://arxiv.org/abs/2404.15923) find
75. Tobias Braun, Mark Rothermel, Marcus Rohrbach, and Anna Rohrbach. Defame: Dynamic evidence-based fact-checking with multimodal experts. arXiv preprint arXiv:2412.10510, 2024. — [arXiv:2412.10510](https://arxiv.org/abs/2412.10510) find
76. Thomas Britton, Cullan Bedwell, Abhijeet Chawhan, Julie Crowe, Naomi Jarvis, Torri Jeske, Nikhil Kalra, David Lawrence, and Diana McSpadden. Ai driven experiment calibration and control. In EPJ Web of Conferences, volume 295, page 02003. EDP Sciences, May 2024. find
77. Victor Brodsky, Ehsan Ullah, Andrey Bychkov, Andrew H Song, Eric E Walk, Peter Louis, Ghulam Rasool, Rajendra S Singh, Faisal Mahmood, Marilyn M Bui, et al. Generative artificial intelligence in anatomic pathology. Archives of Pathology & Laboratory Medicine, Apr 2025. find
78. Qingwen Bu, Jia Zeng, Li Chen, Yanchao Yang, Guyue Zhou, Junchi Yan, Ping Luo, Heming Cui, Yi Ma, and Hongyang Li. Closed-loop visuomotor control with generative expectation for robotic manipulation. In The Thirty-eighth Annual Conference on Neural Information Processing Systems, 2024. find
79. Markus J Buehler. Accelerating scientific discovery with generative knowledge extraction, graph-based representation, and multimodal intelligent graph reasoning. Machine Learning: Science and Technology, 5(3):035083, Sep 2024. find
80. Lukas Buess, Matthias Keicher, Nassir Navab, Andreas Maier, and Soroosh Tayebi Arasteh. From large language models to multimodal ai: A scoping review on the potential of generative ai in medicine. arXiv preprint arXiv:2502.09242, 2025. — [arXiv:2502.09242](https://arxiv.org/abs/2502.09242) find
81. Charlotte Bunne, Yusuf Roohani, Yanay Rosen, Ankit Gupta, Xikun Zhang, Marcel Roed, Theo Alexandrov, Mohammed AlQuraishi, Patricia Brennan, Daniel B Burkhardt, et al. How to build the virtual cell with artificial intelligence: Priorities and opportunities. Cell, 187(25):7045–7063, Dec 2024. find
82. James Burgess, Jeffrey J Nirschl, Laura Bravo-Sánchez, Alejandro Lozano, Sanket Rajan Gupte, Jesus G Galaz-Montoya, Yuhui Zhang, Yuchang Su, Disha Bhowmik, Zachary Coman, et al. Microvqa: A multimodal reasoning benchmark for microscopy-based scientific research. In Proceedings of the Computer Vision… find
83. Keith T Butler, Daniel W Davies, Hugh Cartwright, Olexandr Isayev, and Aron Walsh. Machine learning for molecular and materials science. Nature, 559(7715):547–555, Jul 2018. find
84. Necva Bölücü, Yunus Can Bilge, Dilber Çetintaş, and Zehra Yücel. Modest: A dataset for multi domain scientific title generation. Knowledge-Based Systems, 321:113557, Jun 2025. ISSN 0950-7051. doi: https://doi.org/10.1016/j.knosys.2025.113557. URL https://www.sciencedirect.com/ science/article/pii/S0… — [doi:10.1016/j.knosys.2025.113557](https://doi.org/10.1016/j.knosys.2025.113557) ↗
85. Yi Cai and Gerhard Wunder. On gradient-like explanation under a black-box setting: when black-box explanations become as good as white-box. arXiv preprint arXiv:2308.09381, 2023. — [arXiv:2308.09381](https://arxiv.org/abs/2308.09381) find
86. Reyes Calderon and Francisco Herrera. And plato met chatgpt: an ethical reflection on the use of chatbots in scientific research writing, with a particular focus on the social sciences. Humanities and Social Sciences Communications, 12(1):1–13, May 2025. find
87. Richard B Canty, Jeffrey A Bennett, Keith A Brown, Tonio Buonassisi, Sergei V Kalinin, John R Kitchin, Benji Maruyama, Robert G Moore, Joshua Schrier, Martin Seifrid, et al. Science acceleration and accessibility with self-driving labs. Nature Communications, 16(1):3856, Apr 2025. find
88. Lang Cao and Hanbing Liu. Tablemaster: A recipe to advance table understanding with language models. arXiv preprint arXiv:2501.19378, 2025. — [arXiv:2501.19378](https://arxiv.org/abs/2501.19378) find
89. Shuxiang Cao, Zijian Zhang, Mohammed Alghadeer, Simone D Fasciati, Michele Piscitelli, Mustafa Bakr, Peter Leek, and Alán Aspuru-Guzik. Agents for self-driving laboratories applied to quantum computing. arXiv preprint arXiv:2412.07978, 2024. — [arXiv:2412.07978](https://arxiv.org/abs/2412.07978) find
90. Stanley Cao and Kevin Liu. Figuring out figures: Using textual references to caption scientific figures. arXiv preprint arXiv:2407.11008, 2024. — [arXiv:2407.11008](https://arxiv.org/abs/2407.11008) find
91. Yupeng Cao, Aishwarya Muralidharan Nair, Elyon Eyimife, Nastaran Jamalipour Soofi, KP Subbalakshmi, John R Wullert II, Chumki Basu, and David Shallcross. Can large language models detect misinformation in scientific news reporting? arXiv preprint arXiv:2402.14268, 2024. — [arXiv:2402.14268](https://arxiv.org/abs/2402.14268) find
92. Ege Yiğit Çelik and Selma Tekir. Citebart: Learning to generate citations for local citation recommendation. arXiv preprint arXiv:2412.17534, 2024. find
93. Tuhin Chakrabarty, Philippe Laban, Divyansh Agarwal, Smaranda Muresan, and Chien-Sheng Wu. Art or artifice? large language models and the false promise of creativity. In Proceedings of the 2024 CHI Conference on Human Factors in Computing Systems, pages 1–34, May 2024. find
94. Eric Chamoun, Michael Schlichtkrull, and Andreas Vlachos. Automated focused feedback generation for scientific writing assistance. In Lun-Wei Ku, Andre Martins, and Vivek Srikumar, editors, Findings of the Association for Computational Linguistics: ACL 2024, pages 9742–9763, Bangkok, Thailand, Augus… find
95. Jun Shern Chan, Neil Chowdhury, Oliver Jaffe, James Aung, Dane Sherburn, Evan Mays, Giulio Starace, Kevin Liu, Leon Maksin, Tejal Patwardhan, et al. Mle-bench: Evaluating machine learning agents on machine learning engineering. arXiv preprint arXiv:2410.07095, 2024.
96. Mohit Chandra, Suchismita Naik, Denae Ford, Ebele Okoli, Munmun De Choudhury, Mahsa Ershadi, Gonzalo Ramos, Javier Hernandez, Ananya Bhattacharjee, Shahed Warreth, et al. From lived experience to insight: Unpacking the psychological risks of using ai conversational agents. arXiv preprint arXiv:2412.… — [arXiv:2412.07951](https://arxiv.org/abs/2412.07951) find
97. Yifan Chang, Yukang Feng, Jianwen Sun, Jiaxin Ai, Chuanhao Li, S Kevin Zhou, and Kaipeng Zhang. Sridbench: Benchmark of scientific research illustration drawing of image generation model. arXiv preprint arXiv:2505.22126, 2025. — [arXiv:2505.22126](https://arxiv.org/abs/2505.22126) find
98. Yuan Chang, Ziyue Li, Hengyuan Zhang, Yuanbo Kong, Yanru Wu, Zhijiang Guo, and Ngai Wong. Treereview: A dynamic tree of questions framework for deep and efficient llm-based scientific peer review. arXiv preprint arXiv:2506.07642, 2025.
99. Laurent Charlin and Richard Zemel. The toronto paper matching system: an automated paper-reviewer assignment system. May 2013. find
100. Laurent Charlin, Richard Zemel, and Craig Boutilier. A framework for optimizing paper matching. In Proceedings of the Twenty-Seventh Conference on Uncertainty in Artificial Intelligence, pages 86–95, Jul 2011. find
101. Rajdip Chaudhuri. Llm based exploratory data analysis using bigquery data canvas, Oct 2024. URL https://medium.com/google-cloud/ llm-based-exploratory-data-analysis-using-bigquery-data-canvas-42fbecb9f009. LLM Based Exploratory Data Analysis Using BigQuery Data Canvas. ↗
102. Chi Chen, Weike Ye, Yunxing Zuo, Chen Zheng, and Shyue Ping Ong. Graph networks as a universal machine learning framework for molecules and crystals. Chemistry of Materials, 31(9):3564–3572, Apr 2019. find
103. Hui Chen, Miao Xiong, Yujie Lu, Wei Han, Ailin Deng, Yufei He, Jiaying Wu, Yibo Li, Yue Liu, and Bryan Hooi. Mlr-bench: Evaluating ai agents on open-ended machine learning research. arXiv preprint arXiv:2505.19955, 2025. find
104. Jingqiang Chen and Hai Zhuge. Automatic generation of related work through summarizing citations. Concurrency and Computation: Practice and Experience, 31(3):e4261, Sep 2019. find
105. Junlan Chen, Kexin Zhang, Daifeng Li, Yangyang Feng, Yuxuan Zhang, and Bowen Deng. Structuring scientific innovation: A framework for modeling and discovering impactful knowledge combinations. arXiv preprint arXiv:2503.18865, 2025. — [arXiv:2503.18865](https://arxiv.org/abs/2503.18865) find
106. Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Ponde De Oliveira Pinto, Jared Kaplan, Harri Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, et al. Evaluating large language models trained on code. arXiv preprint arXiv:2107.03374, 2021.
107. Nuo Chen, Andre Lin HuiKai, Jiaying Wu, Junyi Hou, Zining Zhang, Qian Wang, Xidong Wang, and Bingsheng He. Xtragpt: Llms for human-ai collaboration on controllable academic paper revision. arXiv preprint arXiv:2505.11336, 2025. — [arXiv:2505.11336](https://arxiv.org/abs/2505.11336) find
108. Qiguang Chen, Libo Qin, Jiaqi Wang, Jingxuan Zhou, and Wanxiang Che. Unlocking the capabilities of thought: A reasoning boundary framework to quantify and optimize chain-of-thought. Advances in Neural Information Processing Systems, 37:54872–54904, Sep 2024. URL https://proceedings.neurips.cc/paper_… ↗
109. Qiguang Chen, Libo Qin, Jin Zhang, Zhi Chen, Xiao Xu, and Wanxiang Che. M 3 CoT: A novel benchmark for multi-domain multi-step multi-modal chain-of-thought. pages 8199–8221, August 2024. doi: 10.18653/v1/2024.acl-long.446. URL https://aclanthology.org/2024.acl-long.446/. ↗
110. Qiguang Chen, Libo Qin, Jinhao Liu, Yue Liao, Jiaqi Wang, Jingxuan Zhou, and Wanxiang Che. Rbf++: Quantifying and optimizing reasoning boundaries across measurable and unmeasurable capabilities for chain-of-thought reasoning. arXiv preprint arXiv:2505.13307, 2025. — [arXiv:2505.13307](https://arxiv.org/abs/2505.13307) find
111. Qiguang Chen, Libo Qin, Jinhao Liu, Dengyun Peng, Jiannan Guan, Peng Wang, Mengkang Hu, Yuhang Zhou, Te Gao, and Wangxiang Che. Towards reasoning era: A survey of long chain-of-thought for reasoning large language models. arXiv preprint arXiv:2503.09567, 2025.
112. Qiguang Chen, Libo Qin, Jinhao Liu, Dengyun Peng, Jiaqi Wang, Mengkang Hu, Zhi Chen, Wanxiang Che, and Ting Liu. Ecm: A unified electronic circuit model for explaining the emergence of in-context learning and chain-of-thought in large language model. arXiv preprint arXiv:2502.03325, 2025. — [arXiv:2502.03325](https://arxiv.org/abs/2502.03325) find
113. Renqi Chen, Haoyang Su, Shixiang Tang, Zhenfei Yin, Qi Wu, Hui Li, Ye Sun, Nanqing Dong, Wanli Ouyang, and Philip Torr. Ai-driven automation can become the foundation of next-era science of science research. arXiv preprint arXiv:2505.12039, 2025. — [arXiv:2505.12039](https://arxiv.org/abs/2505.12039) find
114. Wei Chen, Han Ding, Meng Yuan, Zhao Zhang, Deqing Wang, and Fuzhen Zhuang. Bridging social psychology and llm reasoning: Conflict-aware meta-review generation via cognitive alignment. arXiv preprint arXiv:2503.13879, 2025. find
115. Wenhu Chen, Ming Yin, Max Ku, Pan Lu, Yixin Wan, Xueguang Ma, Jianyu Xu, Xinyi Wang, and Tony Xia. Theoremqa: A theorem-driven question answering dataset. arXiv preprint arXiv:2305.12524, 2023.
116. Xiaodong Chen, Jillian M Buriak, Mathieu Salanne, and Huolin Xin. Nano & ai: A nobel partnership, Nov 2024. find
117. Xinyun Chen, Maxwell Lin, Nathanael Schärli, and Denny Zhou. Teaching large language models to self-debug. arXiv preprint arXiv:2304.05128, 2023. find
118. Xiuying Chen, Hind Alamro, Mingzhe Li, Shen Gao, Xiangliang Zhang, Dongyan Zhao, and Rui Yan. Capturing relations between scientific papers: An abstractive model for related work section generation. In Chengqing Zong, Fei Xia, Wenjie Li, and Roberto Navigli, editors, Proceedings of the 59th Annual M… find
119. Xiuying Chen, Hind Alamro, Mingzhe Li, Shen Gao, Rui Yan, Xin Gao, and Xiangliang Zhang. Target-aware abstractive related work generation with contrastive learning. In Proceedings of the 45th international ACM SIGIR conference on research and development in information retrieval, pages 373–383, Jul… find
120. Xiuying Chen, Tairan Wang, Taicheng Guo, Kehan Guo, Juexiao Zhou, Haoyang Li, Mingchen Zhuge, Jürgen Schmidhuber, Xin Gao, and Xiangliang Zhang. Scholarchemqa: Unveiling the power of language models in chemical research question answering. arXiv preprint arXiv:2407.16931, 2024.
121. Yaoyu Chen, Yuheng Hu, and Yingda Lu. Predicting field experiments with large language models. arXiv preprint arXiv:2504.01167, 2025. — [arXiv:2504.01167](https://arxiv.org/abs/2504.01167) find
122. Yen-Chun Chen, Linjie Li, Licheng Yu, Ahmed El Kholy, Faisal Ahmed, Zhe Gan, Yu Cheng, and Jingjing Liu. Uniter: Universal image-text representation learning. In European conference on computer vision, pages 104–120. Springer, Sep 2020.
123. Ying-Jung Chen, Ahmad Albarqawi, and Chi-Sheng Chen. Reinforcing clinical decision support through multi-agent systems and ethical ai governance. arXiv preprint arXiv:2504.03699, 2025. — [arXiv:2504.03699](https://arxiv.org/abs/2504.03699) find
124. Yiqun Chen and James Zou. Genept: a simple but effective foundation model for genes and cells built from chatgpt. bioRxiv, pages 2023–10, Mar 2024. find
125. Yiting Chen, Tracy Xiao Liu, You Shan, and Songfa Zhong. The emergence of economic rationality of gpt. Proceedings of the National Academy of Sciences, 120(51):e2316205120, Dec 2023. find
126. Zhi Chen, Qiguang Chen, Libo Qin, Qipeng Guo, Haijun Lv, Yicheng Zou, Wanxiang Che, Hang Yan, Kai Chen, and Dahua Lin. What are the essential factors in crafting effective long context multi-hop instruction datasets? insights and best practices. arXiv preprint arXiv:2409.01893, 2024.
127. Ziru Chen, Shijie Chen, Yuting Ning, Qianheng Zhang, Boshi Wang, Botao Yu, Yifei Li, Zeyi Liao, Chen Wei, Zitong Lu, et al. Scienceagentbench: Toward rigorous assessment of language agents for data-driven scientific discovery. arXiv preprint arXiv:2410.05080, 2024. find
128. Adam Cheng, Aaron Calhoun, and Gabriel Reedy. Artificial intelligence-assisted academic writing: recommendations for ethical use. Advances in Simulation, 10(1):22, Apr 2025. find
129. Junyan Cheng, Peter Clark, and Kyle Richardson. Language modeling by language models. arXiv preprint arXiv:2506.20249, 2025. find
130. Lu Cheng, Ahmadreza Mosallanezhad, Paras Sheth, and Huan Liu. Causal learning for socially responsible ai. arXiv preprint arXiv:2104.12278, 2021. — [arXiv:2104.12278](https://arxiv.org/abs/2104.12278) find
131. Xiaoqing Cheng, Ruizhe Chen, Hongying Zan, Yuxiang Jia, and Min Peng. Biasfilter: An inference-time debiasing framework for large language models. arXiv preprint arXiv:2505.23829, 2025. find
132. Xusen Cheng and Lulu Zhang. Ai-generated literature reviews threaten scientific progress. Nature, 641(8064):852–852, 2025. find
133. Zhi-Qi Cheng, Qi Dai, and Alexander G Hauptmann. Chartreader: A unified framework for chart derendering and comprehension without heuristic rules. In Proceedings of the IEEE/CVF International Conference on Computer Vision, pages 22202–22213, Apr 2023. find
134. Zihui Cheng, Qiguang Chen, Xiao Xu, Jiaqi Wang, Weiyun Wang, Hao Fei, Yidong Wang, Alex Jinpeng Wang, Zhi Chen, Wanxiang Che, et al. Visual thoughts: A unified perspective of understanding multimodal chain-of-thought. arXiv preprint arXiv:2505.15510, 2025. — [arXiv:2505.15510](https://arxiv.org/abs/2505.15510) find
135. Zihui Cheng, Qiguang Chen, Jin Zhang, Hao Fei, Xiaocheng Feng, Wanxiang Che, Min Li, and Libo Qin. Comt: A novel benchmark for chain of multi-modal thought on large vision-language models. In Proceedings of the AAAI Conference on Artificial Intelligence, volume 39, pages 23678–23686, Apr 2025. find
136. Jaewoong Choi and Byungju Lee. Accelerating materials language processing with large language models. Communications Materials, 5(1):13, Feb 2024. find
137. Zheng Chu, Huiming Fan, Jingchang Chen, Qianyu Wang, Mingda Yang, Jiafeng Liang, Zhongjie Wang, Hao Li, Guo Tang, Ming Liu, et al. Self-critique guided iterative reasoning for multi-hop question answering. arXiv preprint arXiv:2505.19112, 2025. find
138. Zhumin Chu, Qingyao Ai, Yiteng Tu, Haitao Li, and Yiqun Liu. Automatic large language model evaluation via peer review. In Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, pages 384–393, Oct 2024. find
139. Zhumin Chu, Qingyao Ai, Yiteng Tu, Haitao Li, and Yiqun Liu. Pre: A peer review based large language model evaluator. arXiv preprint arXiv:2401.15641, 2024. — [arXiv:2401.15641](https://arxiv.org/abs/2401.15641) find
140. Lynn Chua, Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chulin Xie, and Chiyuan Zhang. Crosslingual capabilities and knowledge barriers in multilingual large language models. arXiv preprint arXiv:2406.16135, 2024. — [arXiv:2406.16135](https://arxiv.org/abs/2406.16135) find
141. Ilker Cingillioglu, Uri Gal, and Artem Prokhorov. Ai-experiments in education: An ai-driven randomized controlled trial for higher education research. Education and Information Technologies, 29(15):19649– 19677, 2024. find
142. Defne Circi, Ghazal Khalighinejad, Anlan Chen, Bhuwan Dhingra, and L Catherine Brinson. How well do large language models understand tables in materials science? Integrating Materials and Manufacturing Innovation, 13(3):669–687, Jul 2024. URL https://link.springer.com/article/10. 1007/s40192-024-003… ↗
143. Davide Cirillo, Iker Núñez-Carpintero, and Alfonso Valencia. Artificial intelligence in cancer research: learning at different levels of data granularity. Molecular oncology, 15(4):817–829, Apr 2021. find
144. Christopher Clark, Kenton Lee, Ming-Wei Chang, Tom Kwiatkowski, Michael Collins, and Kristina Toutanova. Boolq: Exploring the surprising difficulty of natural yes/no questions. arXiv preprint arXiv:1905.10044, 2019.
145. Andy Coenen, Luke Davis, Daphne Ippolito, Emily Reif, and Ann Yuan. Wordcraft: A human-ai collaborative editor for story writing. arXiv preprint arXiv:2107.07430, 2021. — [arXiv:2107.07430](https://arxiv.org/abs/2107.07430) find
146. Kai-Hendrik Cohrs, Emiliano Diaz, Vasileios Sitokonstantinou, Gherardo Varando, and Gustau Camps-Valls. Large language models for causal hypothesis generation in science. Machine Learning: Science and Technology, 6(1):013001, Jan 2025. find
147. Alexis Conneau, Kartikay Khandelwal, Naman Goyal, Vishrav Chaudhary, Guillaume Wenzek, Francisco Guzmán, Edouard Grave, Myle Ott, Luke Zettlemoyer, and Veselin Stoyanov. Unsupervised cross-lingual representation learning at scale. arXiv preprint arXiv:1911.02116, 2019. find
148. Micaela E Consens, Cameron Dufault, Michael Wainberg, Duncan Forster, Mehran Karimzadeh, Hani Goodarzi, Fabian J Theis, Alan Moses, and Bo Wang. Transformers and genome language models. Nature Machine Intelligence, pages 1–17, Mar 2025. find
149. Paulo Henrique Couto, Quang Phuoc Ho, Nageeta Kumari, Benedictus Kent Rachmat, Thanh Gia Hieu Khuong, Ihsan Ullah, and Lisheng Sun-Hosoya. Relevai-reviewer: A benchmark on ai reviewers for survey paper relevance. arXiv preprint arXiv:2406.10294, 2024. — [arXiv:2406.10294](https://arxiv.org/abs/2406.10294) find
150. Douglas B Craig. A human-LLM note-taking system with case-based reasoning as framework for scientific discovery. In Peter Jansen, Bhavana Dalvi Mishra, Harsh Trivedi, Bodhisattwa Prasad Majumder, Tom Hope, Tushar Khot, Doug Downey, and Eric Horvitz, editors, Proceedings of the 1st Workshop on AI and… find
151. Miles Cranmer, Sam Greydanus, Stephan Hoyer, Peter Battaglia, David Spergel, and Shirley Ho. Lagrangian neural networks. arXiv preprint arXiv:2003.04630, 2020. — [arXiv:2003.04630](https://arxiv.org/abs/2003.04630) find
152. Haotian Cui, Chloe Wang, Hassaan Maan, Kuan Pang, Fengning Luo, Nan Duan, and Bo Wang. scgpt: toward building a foundation model for single-cell multi-omics using generative ai. Nature Methods, 21(8):1470–1480, Feb 2024. find
153. Haotian Cui, Yue Xu, Kuan Pang, Gen Li, Fanglin Gong, Bo Wang, and Bowen Li. Lumi-lab: a foundation model-driven autonomous platform enabling discovery of new ionizable lipid designs for mrna delivery. BioRxiv, pages 2025–02, Feb 2025. find
154. Ziyan Cui, Ning Li, and Huaikang Zhou. Can ai replace human subjects? a large-scale replication of psychological experiments with llms. arXiv preprint arXiv:2409.00128, 2024. — [arXiv:2409.00128](https://arxiv.org/abs/2409.00128) find
155. Tianwei Dai, Sriram Vijayakrishnan, Filip T Szczypiński, Jean-François Ayme, Ehsan Simaei, Thomas Fellowes, Rob Clowes, Lyubomir Kotopanov, Caitlin E Shields, Zhengxue Zhou, et al. Autonomous mobile robots for exploratory synthetic chemistry. Nature, pages 1–8, Nov 2024. find
156. Yahao Dai, Henry Chan, Aikaterini Vriza, Fredrick Kim, Yunfei Wang, Wei Liu, Naisong Shan, Jing Xu, Max Weires, Yukun Wu, et al. Adaptive ai decision interface for autonomous electronic material discovery. arXiv preprint arXiv:2504.13344, 2025. — [arXiv:2504.13344](https://arxiv.org/abs/2504.13344) find
157. Preetam Prabhu Srikar Dammu, Himanshu Naidu, Mouly Dewan, YoungMin Kim, Tanya Roosta, Aman Chadha, and Chirag Shah. Claimver: Explainable claim-level verification and evidence attribution of text through knowledge graphs. arXiv preprint arXiv:2403.09724, 2024. find
158. Raghav Dangayach, Nohyeong Jeong, Elif Demirel, Nigmet Uzal, Victor Fung, and Yongsheng Chen. Machine learning-aided inverse design and discovery of novel polymeric materials for membrane separation. Environmental Science & Technology, 59(2):993–1012, Dec 2024. find
159. Mike D’Arcy, Tom Hope, Larry Birnbaum, and Doug Downey. Marg: Multi-agent review generation for scientific papers. arXiv preprint arXiv:2401.04259, 2024. find
160. Maxime Darrin, Ines Arous, Pablo Piantanida, and Jackie CK Cheung. Glimpse: Pragmatically informative multi-document summarization for scholarly reviews. arXiv preprint arXiv:2406.07359, 2024. find
161. Kourosh Darvish, Marta Skreta, Yuchi Zhao, Naruki Yoshikawa, Sagnik Som, Miroslav Bogdanovic, Yang Cao, Han Hao, Haoping Xu, Alán Aspuru-Guzik, et al. Organa: a robotic assistant for automated chemistry experimentation and characterization. Matter, 8(2), Feb 2025. find
162. Anubrata Das, Houjiang Liu, Venelin Kovatchev, and Matthew Lease. The state of human-centered nlp technology for fact-checking. Information processing & management, 60(2):103219, Mar 2023. find
163. Debajyoti Dasgupta, Arijit Mondal, and Partha Pratim Chakrabarti. Empowering ai as autonomous researchers: Evaluating llms in generating novel research ideas through automated metrics. In 2nd AI4Research Workshop: Towards a Knowledge-grounded Scientific Research Lifecycle, Dec 2024. find
164. Filipe de Avila Belbute-Peres, Kevin Smith, Kelsey Allen, Josh Tenenbaum, and J Zico Kolter. End-to-end differentiable physics for learning and control. Advances in Neural Information Processing Systems, 31, Dec 2018. find
165. Nicola De Cao and Thomas Kipf. Molgan: An implicit generative model for small molecular graphs. arXiv preprint arXiv:1805.11973, 2018. — [arXiv:1805.11973](https://arxiv.org/abs/1805.11973) find
166. Ties de Kok. Chatgpt for textual analysis? how to use generative llms in accounting research. Management Science, Jan 2025. doi: 10.1287/mnsc.2023.03253. URL https://doi.org/10. 1287/mnsc.2023.03253. Published online in Articles in Advance, 13 Jan 2025. — [doi:10.1287/mnsc.2023.03253](https://doi.org/10.1287/mnsc.2023.03253) find
167. Michael S. Deiner, Vlad Honcharov, Jiawei Li, Tim K. Mackey, Travis C. Porco, and Urmimala Sarkar. Large language models can enable inductive thematic analysis of a social media corpus in a single prompt: Human validation study. JMIR Infodemiology, 4:e59641, August 2024. doi: 10.2196/59641. URL http… — [doi:10.2196/59641](https://doi.org/10.2196/59641) find
168. Zekun Deng, Zixin Zeng, Weiye Gu, Jiawen Ji, and Bolin Hua. Automatic related work section generation by sentence extraction and reordering. In AII@ iConference, pages 101–110, Jan 2021. find
169. Saaketh Desai, Sadhvikas Addamane, Jeffrey Y Tsao, Igal Brener, Laura P Swiler, Remi Dingreville, and Prasad P Iyer. Autoscilab: A self-driving laboratory for interpretable scientific discovery. In Proceedings of the AAAI Conference on Artificial Intelligence, volume 39, pages 146–154, Apr 2025. find
170. Jay DeYoung, Iz Beltagy, Madeleine van Zuylen, Bailey Kuehl, and Lucy Lu Wang. Ms2: Multi-document summarization of medical studies. arXiv preprint arXiv:2104.06486, 2021. — [arXiv:2104.06486](https://arxiv.org/abs/2104.06486) find
171. Oscar Díaz, Xabier Garmendia, and Juanan Pereira. Streamlining the review process: Ai-generated annotations in research manuscripts. arXiv preprint arXiv:2412.00281, 2024. — [arXiv:2412.00281](https://arxiv.org/abs/2412.00281) find
172. Danica Dillion, Niket Tandon, Yuling Gu, and Kurt Gray. Can ai language models replace human participants? Trends in Cognitive Sciences, 27(7):597–600, Jul 2023. ISSN 1364-6613. doi: https://doi.org/10.1016/j.tics.2023.04.008. URL https://www.sciencedirect.com/ science/article/pii/S1364661323000980. — [doi:10.1016/j.tics.2023.04.008](https://doi.org/10.1016/j.tics.2023.04.008) ↗
173. Ning Ding, Shang Qu, Linhai Xie, Yifei Li, Zaoqu Liu, Kaiyan Zhang, Yibai Xiong, Yuxin Zuo, Zhangren Chen, Ermo Hua, et al. Automating exploratory proteomics research via language models. arXiv preprint arXiv:2411.03743, 2024. find
174. Ying Ding and Blaise Cronin. Popular and/or prestigious? measures of scholarly esteem. Information processing & management, 47(1):80–96, Jan 2011. find
175. Martin Docekal, Martin Fajcik, and Pavel Smrz. Oarelatedwork: A large-scale dataset of related work sections with full-texts from open access sources. arXiv preprint arXiv:2405.01930, 2024. find
176. Schmidt Dominik, Jiang Zhengyao, and Wu Yuxiang. Aide: Human-level performance on data science competitions, Apr 2023. URL https://www.weco.ai/blog/technical-report. AIDE. ↗
177. Tommaso Dorigo, Andrea Giammanco, Pietro Vischia, Max Aehle, Mateusz Bawaj, Alexey Boldyrev, Pablo de Castro Manzano, Denis Derkach, Julien Donini, Auralee Edelen, et al. Toward the end-to-end optimization of particle physics instruments with differentiable programming. Reviews in Physics, 10: 10008… find
178. Bohdana Doskaliuk, Olena Zimba, Marlen Yessirkepov, Iryna Klishch, and Roman Yatsyshyn. Artificial intelligence in peer review: enhancing efficiency while preserving integrity. Journal of Korean medical science, 40(7), Feb 2025. find
179. Ryan S Dove, Roy J Hartfield, and Mark Carpenter. Semi-supervised classification with novelty detection using support vector machines and linear discriminant analysis. In AIAA SCITECH 2025 Forum, page 0705, Jan 2025. find
180. Jiangshu Du, Yibo Wang, Wenting Zhao, Zhongfen Deng, Shuaiqi Liu, Renze Lou, Henry Peng Zou, Pranav Narayanan Venkit, Nan Zhang, Mukund Srinath, Haoran Ranran Zhang, Vipul Gupta, Yinghui Li, Tao Li, Fei Wang, Qin Liu, Tianlin Liu, Pengzhi Gao, Congying Xia, Chen Xing, Cheng Jiayang, Zhaowei Wang, Yi… — LLMs Assist NLP Researchers: Critique Paper (Meta-)Reviewing
181. Mingxuan Du, Benfeng Xu, Chiwei Zhu, Xiaorui Wang, and Zhendong Mao. Deepresearch bench: A comprehensive benchmark for deep research agents. arXiv preprint arXiv:2506.11763, 2025.
182. Wanyu Du, Zae Myung Kim, Vipul Raheja, Dhruv Kumar, and Dongyeop Kang. Read, revise, repeat: A system demonstration for human-in-the-loop iterative text revision. arXiv preprint arXiv:2204.03685, 2022. find
183. Nils Dycke, Ilia Kuznetsov, and Iryna Gurevych. NLPeer: A unified resource for the computational study of peer review. In Anna Rogers, Jordan Boyd-Graber, and Naoaki Okazaki, editors, Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pag…
184. Sana Ebrahimi, Kaiwen Chen, Abolfazl Asudeh, Gautam Das, and Nick Koudas. Axolotl: fairness through assisted self-debiasing of large language model outputs. arXiv preprint arXiv:2403.00198, 2024. — [arXiv:2403.00198](https://arxiv.org/abs/2403.00198) find
185. Brice Edelman and Jeffrey Skolnick. Valsci: an open-source, self-hostable literature review utility for automated large-batch scientific claim verification using large language models. BMC bioinformatics, 26(1):1–25, May 2025. find
186. Kristina Edfeldt, Aled M Edwards, Ola Engkvist, Judith Günther, Matthew Hartley, David G Hulcoop, Andrew R Leach, Brian D Marsden, Amelie Menge, Leonie Misquitta, et al. A data science roadmap for open science organizations engaged in early-stage drug discovery. Nature Communications, 15(1): 5640, J… find
187. Steffen Eger, Yong Cao, Jennifer D’Souza, Andreas Geiger, Christian Greisinger, Stephanie Gross, Yufang Hou, Brigitte Krenn, Anne Lauscher, Yizhi Li, et al. Transforming science with large language models: A survey on ai-assisted scientific discovery, experimentation, content generation, and evaluat… — Transforming Science with Large Language Models: A Survey on AI-assisted Scientific Discovery, Experimentation, Content Generation, and Evaluation
188. Upol Ehsan and Mark Riedl. Explainable ai reloaded: Challenging the xai status quo in the era of large language models. In Proceedings of the Halfway to the Future Symposium, pages 1–8, Oct 2024. find
189. Christelle Ekosso, Hao Liu, Avery Glagovich, Dustin Nguyen, Sarah Maurer, and Joshua Schrier. Accelerating the discovery of abiotic vesicles with ai-guided automated experimentation. Langmuir, 41(1):858–867, 2024. find
190. Islam Eldifrawi, Shengrui Wang, and Amine Trabelsi. Automated justification production for claim veracity in fact checking: A survey on architectures and approaches. arXiv preprint arXiv:2407.12853, 2024. find
191. Felix Faltings, Michel Galley, Gerold Hintz, Chris Brockett, Chris Quirk, Jianfeng Gao, and Bill Dolan. Text editing by command. arXiv preprint arXiv:2010.12826, 2020. find
192. Angela Fan and Claire Gardent. Generating full length wikipedia biographies: The impact of gender bias on the retrieval-based generation of women biographies. arXiv preprint arXiv:2204.05879, 2022. — [arXiv:2204.05879](https://arxiv.org/abs/2204.05879) find
193. Angela Fan, Beliz Gokkaya, Mark Harman, Mitya Lyubarskiy, Shubho Sengupta, Shin Yoo, and Jie M Zhang. Large language models for software engineering: Survey and open problems. In 2023 IEEE/ACM International Conference on Software Engineering: Future of Software Engineering (ICSE-FoSE), pages 31–53.… find
194. Wenqi Fan, Yujuan Ding, Liangbo Ning, Shijie Wang, Hengyun Li, Dawei Yin, Tat-Seng Chua, and Qing Li. A survey on rag meeting llms: Towards retrieval-augmented large language models. In Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, pages 6491–6501, Aug 2024.
195. Zhihao Fan, Jialong Tang, Wei Chen, Siyuan Wang, Zhongyu Wei, Jun Xi, Fei Huang, and Jingren Zhou. Ai hospital: Benchmarking large language models in a multi-agent medical interaction simulator. arXiv preprint arXiv:2402.09742, 2024.
196. You-Le Fang, Dong-Shan Jian, Xiang Li, and Yan-Qing Ma. Ai-newton: A concept-driven physical law discovery system without prior physical knowledge. arXiv preprint arXiv:2504.01538, 2025. — [arXiv:2504.01538](https://arxiv.org/abs/2504.01538) find
197. Shai Farber. Enhancing peer review efficiency: A mixed-methods analysis of artificial intelligence-assisted reviewer selection across academic disciplines. Learned Publishing, 37(4):e1638, Oct 2024. find
198. Shai Farber. Enhancing academic decision-making: A pilot study of ai-supported journal selection in higher education. Innovative Higher Education, pages 1–19, Feb 2025. find
199. Manaal Faruqui, Ellie Pavlick, Ian Tenney, and Dipanjan Das. Wikiatomicedits: A multilingual corpus of wikipedia edits for modeling language and discourse. arXiv preprint arXiv:1808.09422, 2018. find
200. Yao Fehlis. Uncovering bottlenecks and optimizing scientific lab workflows with cycle time reduction agents. arXiv preprint arXiv:2505.21534, 2025. — [arXiv:2505.21534](https://arxiv.org/abs/2505.21534) find
201. Yao Fehlis, Paul Mandel, Charles Crain, Betty Liu, and David Fuller. Accelerating drug discovery with artificial: a whole-lab orchestration and scheduling system for self-driving labs. arXiv preprint arXiv:2504.00986, 2025. — [arXiv:2504.00986](https://arxiv.org/abs/2504.00986) find
202. Bin Feng, Zequn Liu, Nanlan Huang, Zhiping Xiao, Haomiao Zhang, Srbuhi Mirzoyan, Hanwen Xu, Jiaran Hao, Yinghui Xu, Ming Zhang, et al. A bioactivity foundation model using pairwise meta-learning. Nature Machine Intelligence, 6(8):962–974, Aug 2024. find
203. Jingsen Feng, Ran Xu, and Xu Chu. Openfoamgpt 2.0: end-to-end, trustworthy automation for computational fluid dynamics. arXiv preprint arXiv:2504.19338, 2025. find
204. Kehua Feng, Keyan Ding, Weijie Wang, Xiang Zhuang, Zeyuan Wang, Ming Qin, Yu Zhao, Jianhua Yao, Qiang Zhang, and Huajun Chen. Sciknoweval: Evaluating multi-level scientific knowledge of large language models. arXiv preprint arXiv:2406.09098, 2024.
205. KJ Feng, Kevin Pu, Matt Latzke, Tal August, Pao Siangliulue, Jonathan Bragg, Daniel S Weld, Amy X Zhang, and Joseph Chee Chang. Cocoa: Co-planning and co-execution with ai agents. arXiv preprint arXiv:2412.10999, 2024. — [arXiv:2412.10999](https://arxiv.org/abs/2412.10999) find
206. Ruozhu Feng, Yangang Liang, Tianzhixi Yin, Peiyuan Gao, and Wei Wang. Agentic assistant for material scientists. Apr 2025. find
207. Tao Feng, Yihang Sun, and Jiaxuan You. Grapheval: A lightweight graph-based llm framework for idea evaluation. arXiv preprint arXiv:2503.12600, 2025. find
208. Leandro Carísio Fernandes, Gustavo Bartz Guedes, Thiago Soares Laitz, Thales Sales Almeida, Rodrigo Nogueira, Roberto Lotufo, and Jayr Pereira. Surveysum: A dataset for summarizing multiple scientific articles into a survey section. In Brazilian Conference on Intelligent Systems, pages 431–444. Spri… find
209. Emilio Ferrara. Fairness and bias in artificial intelligence: A brief survey of sources, impacts, and mitigation strategies. Sci, 6(1):3, Dec 2023. find
210. Financial Times. Deepmind and biontech build ai lab assistants for scientific research. Financial Times, Oct 2024. URL https://www.ft.com/content/ 64b1bb33-095e-4cc5-a911-50df76fa3d1d. ↗
211. Emily First, Markus N Rabe, Talia Ringer, and Yuriy Brun. Baldur: Whole-proof generation and repair with large language models. In Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, pages 1229–1241, Nov 2023. find
212. Marcio Fonseca and Shay Cohen. Can large language model summarizers adapt to diverse scientific communication goals? In Lun-Wei Ku, Andre Martins, and Vivek Srikumar, editors, Findings of the Association for Computational Linguistics: ACL 2024, pages 8599–8618, Bangkok, Thailand, August 2024. Associ… find
213. Thibault Formal, Carlos Lassance, Benjamin Piwowarski, and Stéphane Clinchant. Splade v2: Sparse lexical and expansion model for information retrieval. arXiv preprint arXiv:2109.10086, 2021.
214. Maria Frasca, Davide La Torre, Gabriella Pravettoni, and Ilaria Cutica. Explainable and interpretable artificial intelligence in medicine: a systematic bibliometric review. Discover Artificial Intelligence, 4 (1):15, Feb 2024. find
215. Simon Frieder, Jonas Bayer, Katherine M Collins, Julius Berner, Jacob Loader, András Juhász, Fabian Ruehle, Sean Welleck, Gabriel Poesia, Ryan-Rhys Griffiths, et al. Data for mathematical copilots: Better ways of presenting proofs for machine learning. arXiv preprint arXiv:2412.15184, 2024. — [arXiv:2412.15184](https://arxiv.org/abs/2412.15184) find
216. Samuel Frontull and Georg Moser. Rule-based, neural and llm back-translation: Comparative insights from a variant of ladin. arXiv preprint arXiv:2407.08819, 2024. find
217. Yongfan Fu, Jian Luo, Guofang Nan, and Dahui Li. Peer review expert group recommendation: A multi-subject coverage-based approach. Expert Systems with Applications, 264:125971, Mar 2025. find
218. Carlo Galli, Chiara Moretti, and Elena Calciolari. Intelligent summaries: Will artificial intelligence mark the finale for biomedical literature reviews? Learned Publishing, Dec 2024. find
219. Shubham Gandhi, Dhruv Shah, Manasi Patwardhan, Lovekesh Vig, and Gautam Shroff. Researchcodeagent: An llm multi-agent system for automated codification of research methodologies. arXiv preprint arXiv:2504.20117, 2025. — [arXiv:2504.20117](https://arxiv.org/abs/2504.20117) find
220. Amrita Ganguly, Aditya Johri, Areej Ali, and Nora McDonald. Generative artificial intelligence for academic research: evidence from guidance issued for researchers by higher education institutions in the united states. AI and Ethics, pages 1–17, Mar 2025. find
221. Debargha Ganguly, Vikash Singh, Sreehari Sankar, Biyao Zhang, Xuecen Zhang, Srinivasan Iyengar, Xiaotian Han, Amit Sharma, Shivkumar Kalyanaraman, and Vipin Chaudhary. Grammars of formal uncertainty: When to trust llms in automated reasoning tasks. arXiv preprint arXiv:2505.20047, 2025. find
222. Amit Gangwal, Azim Ansari, Iqrar Ahmad, Abul Kalam Azad, and Wan Mohd Azizi Wan Sulaiman. Current strategies to address data scarcity in artificial intelligence-based drug discovery: A comprehensive review. Computers in Biology and Medicine, 179:108734, Sep 2024. find
223. Xian Gao, Jiacheng Ruan, Jingsheng Gao, Ting Liu, and Yuzhuo Fu. Reviewagents: Bridging the gap between human and ai-generated paper reviews. arXiv preprint arXiv:2503.08506, 2025. — [arXiv:2503.08506](https://arxiv.org/abs/2503.08506) find
224. Xian Gao, Zongyun Zhang, Mingye Xie, Ting Liu, and Yuzhuo Fu. Graph of ai ideas: Leveraging knowledge graphs and llms for ai research idea generation. arXiv preprint arXiv:2503.08549, 2025. — [arXiv:2503.08549](https://arxiv.org/abs/2503.08549) find
225. Andres Garcia-Silva, Cristian Berrio, Jose Manuel Gomez-Perez, Jose Antonio Martínez-Heras, Alessandro Donati, and Ilaria Roma. Spaceqa: Answering questions about the design of space missions and space craft concepts. In Proceedings of the 45th International ACM SIGIR Conference on Research and Deve… find
226. Daniel Garijo, Qifan Yang, Hernán Vargas, Shruti P Gadewar, Kevin Low, Varun Ratnakar, Maximiliano Osorio, Alyssa H Zhu, Agnes McMahon, Yolanda Gil, et al. Neurodisk: An ai approach to automate continuous inquiry-driven discoveries in neuroimaging genetics. bioRxiv, Feb 2025. find
227. Aniketh Garikaparthi, Manasi Patwardhan, Aditya Sanjiv Kanade, Aman Hassan, Lovekesh Vig, and Arman Cohan. Mir: Methodology inspiration retrieval for scientific research problems. arXiv preprint arXiv:2506.00249, 2025. find
228. Aniketh Garikaparthi, Manasi Patwardhan, Lovekesh Vig, and Arman Cohan. Iris: Interactive research ideation system for accelerating scientific discovery. arXiv preprint arXiv:2504.16728, 2025. find
229. Yubin Ge, Ly Dinh, Xiaofeng Liu, Jinsong Su, Ziyao Lu, Ante Wang, and Jana Diesner. Baco: A background knowledge-and content-based framework for citing sentence generation. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Con… find
230. Mingmeng Geng and Roberto Trotta. Human-llm coevolution: Evidence from academic writing. arXiv preprint arXiv:2502.09606, 2025. find
231. Elizabeth Oommen George. How paperpal enhances english writing quality and improves productivity for japanese academics. Aug 2024. find
232. Katy Ilonka Gero, Vivian Liu, and Lydia Chilton. Sparks: Inspiration for science writing using language models. In Proceedings of the 2022 ACM Designing Interactive Systems Conference, pages 1002–1019, Jun 2022. find
233. Alireza Ghafarollahi and Markus J Buehler. Protagents: protein discovery via large language model multi-agent collaborations combining physics and machine learning. Digital Discovery, 3(7):1389– 1409, May 2024. find
234. Alireza Ghafarollahi and Markus J Buehler. Sciagents: Automating scientific discovery through multi-agent intelligent graph reasoning. arXiv preprint arXiv:2409.05556, 2024. find
235. Alireza Ghafarollahi and Markus J Buehler. Sparks: Multi-agent artificial intelligence model discovers protein design principles. arXiv preprint arXiv:2504.19017, 2025. — [arXiv:2504.19017](https://arxiv.org/abs/2504.19017) find
236. Ali Essam Ghareeb, Benjamin Chang, Ludovico Mitchener, Angela Yiu, Caralyn J Szostkiewicz, Jon M Laurent, Muhammed T Razzak, Andrew D White, Michaela M Hinks, and Samuel G Rodriques. Robin: A multi-agent system for automating scientific discovery. arXiv preprint arXiv:2505.13400. find
237. Ali Gharizadeh, Karim Abbasi, Amin Ghareyazi, Mohammad RK Mofrad, and Hamid R Rabiee. Hgtdr: Advancing drug repurposing with heterogeneous graph transformers. Bioinformatics, 40(7):btae349, Jul 2024. find
238. Tirthankar Ghosal, Sandeep Kumar, Prabhat Kumar Bharti, and Asif Ekbal. Peer review analyze: A novel benchmark resource for computational analysis of peer reviews. Plos one, 17(1):e0259238, Jan 2022. find
239. Asish Ghoshal, Srinivasan Iyer, Bhargavi Paranjape, Kushal Lakhotia, Scott Wen-tau Yih, and Yashar Mehdad. Quaser: Question answering with scalable extractive rationalization. In Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 12… find
240. Karan Girotra, Lennart Meincke, Christian Terwiesch, and Karl T Ulrich. Ideas are dimes a dozen: Large language models for idea generation in innovation. The Wharton School Research Paper Forthcoming, Jul 2023. find
241. Moshe Glickman and Tali Sharot. How human–ai feedback loops alter human perceptual, emotional and social judgements. Nature Human Behaviour, 9(2):345–359, 2025. find
242. Max Glockner, Yufang Hou, and Iryna Gurevych. Missing counter-evidence renders nlp fact-checking unrealistic for misinformation. arXiv preprint arXiv:2210.13865, 2022. find
243. Max Glockner, Yufang Hou, Preslav Nakov, and Iryna Gurevych. Grounding fallacies misrepresenting scientific publications in evidence. arXiv preprint arXiv:2408.12812, 2024. find
244. Ozan Gokdemir, Carlo Siebenschuh, Alexander Brace, Azton Wells, Brian Hsu, Kyle Hippe, Priyanka V Setty, Aswathy Ajith, J Gregory Pauloski, Varuni Sastry, et al. Hiperrag: High-performance retrieval augmented generation for scientific insights. arXiv preprint arXiv:2505.04846, Jun 2025. find
245. Ali Goli and Amandeep Singh. Frontiers: Can large language models capture human preferences? Marketing Science, 43(4):709–722, Apr 2024. doi: 10.1287/mksc.2023.0306. URL https://doi.org/10.1287/mksc.2023.0306. — [doi:10.1287/mksc.2023.0306](https://doi.org/10.1287/mksc.2023.0306) ↗
246. Catalina Gomez, Sue Min Cho, Shichang Ke, Chien-Ming Huang, and Mathias Unberath. Human-ai collaboration is not very collaborative yet: A taxonomy of interaction patterns in ai-assisted decision making from a systematic review. Frontiers in Computer Science, 6:1521066, Jan 2025. find
247. Rafael Gómez-Bombarelli, Jennifer N Wei, David Duvenaud, José Miguel Hernández-Lobato, Benjamín Sánchez-Lengeling, Dennis Sheberla, Jorge Aguilera-Iparraguirre, Timothy D Hirzel, Ryan P Adams, and Alán Aspuru-Guzik. Automatic chemical design using a data-driven continuous representation of molecules… find
248. Jose Manuel Gomez-Perez and Raul Ortega. Look, read and enrich-learning from scientific figures and their captions. In Proceedings of the 10th International Conference on Knowledge Capture, pages 101–108, Sep 2019. find
249. Rubén González-Sendino, Emilio Serrano, and Javier Bajo. Mitigating bias in artificial intelligence: Fair data generation via causal models for transparent and explainable decision-making. Future Generation Computer Systems, 155:384–401, Jun 2024. find
250. Zachary Goodsell and Juhani Yli-Vakkuri. Lf: a foundational higher-order-logic. arXiv preprint arXiv:2401.11050, 2024. — [arXiv:2401.11050](https://arxiv.org/abs/2401.11050) find
251. Diego Gosmar and Deborah A Dahl. Hallucination mitigation using agentic ai natural language-based frameworks. arXiv preprint arXiv:2501.13946, 2025. — [arXiv:2501.13946](https://arxiv.org/abs/2501.13946) find
252. Juraj Gottweis, Wei-Hung Weng, Alexander Daryin, Tao Tu, Anil Palepu, Petar Sirkovic, Artiom Myaskovsky, Felix Weissenberger, Keran Rong, Ryutaro Tanno, et al. Towards an ai co-scientist. arXiv preprint arXiv:2502.18864, 2025.
253. Aaron Grattafiori, Abhimanyu Dubey, Abhinav Jauhri, Abhinav Pandey, Abhishek Kadian, Ahmad Al-Dahle, Aiesha Letman, Akhil Mathur, Alan Schelten, Alex Vaughan, et al. The llama 3 herd of models. arXiv preprint arXiv:2407.21783, 2024.
254. Samuel Greydanus, Misko Dzamba, and Jason Yosinski. Hamiltonian neural networks. Advances in Neural Information Processing Systems, 32, Jul 2019. find
255. Mourad Gridach, Jay Nanavati, Khaldoun Zine El Abidine, Lenon Mendes, and Christina Mack. Agentic ai for scientific discovery: A survey of progress, challenges, and future directions. arXiv preprint arXiv:2503.08979, 2025. — [arXiv:2503.08979](https://arxiv.org/abs/2503.08979) find
256. Antoine Grosnit, Alexandre Maraval, James Doran, Giuseppe Paolo, Albert Thomas, Refinath Shahul Hameed Nabeezath Beevi, Jonas Gonzalez, Khyati Khandelwal, Ignacio Iacobacci, Abdelhakim Benechehab, et al. Large language models orchestrating structured reasoning achieve kaggle grandmaster level. arXiv… — [arXiv:2411.03562](https://arxiv.org/abs/2411.03562) find
257. Ken Gu, Ruoxi Shang, Ruien Jiang, Keying Kuang, Richard-John Lin, Donghe Lyu, Yue Mao, Youran Pan, Teng Wu, Jiaqian Yu, et al. Blade: Benchmarking language model agents for data-driven science. arXiv preprint arXiv:2408.09667, 2024. find
258. Nianlong Gu and Richard HR Hahnloser. Controllable citation sentence generation with language models. arXiv preprint arXiv:2211.07066, 2022. find
259. Tianyang Gu, Jingjin Wang, Zhihao Zhang, and HaoHong Li. Llms can realize combinatorial creativity: generating creative ideas via llms for scientific research. arXiv preprint arXiv:2412.14141, 2024. — [arXiv:2412.14141](https://arxiv.org/abs/2412.14141) find
260. Xuemei Gu and Mario Krenn. Generation and human-expert evaluation of interesting research ideas using knowledge graphs and large language models. arXiv preprint arXiv:2405.17044, 2024. — [arXiv:2405.17044](https://arxiv.org/abs/2405.17044) find
261. Yuan Guan, Jakkapong Inchai, Zhuoqing Fang, Jacky Law, Alberto Alonzo Garcia Brito, Annalisa Pawlosky, Juraj GottWeis, Alexander Daryin, Artiom Myaskovsky, Anil Palepu, et al. Ai-assisted drug re-purposing for human liver fibrosis. bioRxiv, pages 2025–04, May 2025. find
262. Badra Souhila Guendouzi, Samir Ouchani, Hiba EL Assaad, and Madeleine EL Zaher. A systematic review of federated learning: Challenges, aggregation methods, and development tools. Journal of Network and Computer Applications, 220:103714, Nov 2023. find
263. Maeva Guerrier, Karthik Soma, Hassan Fouad, and Giovanni Beltrame. Guided by guardrails: Control barrier functions as safety instructors for robotic learning. arXiv preprint arXiv:2505.18858, 2025. — [arXiv:2505.18858](https://arxiv.org/abs/2505.18858) find
264. Daya Guo, Qihao Zhu, Dejian Yang, Zhenda Xie, Kai Dong, Wentao Zhang, Guanting Chen, Xiao Bi, Yu Wu, YK Li, et al. Deepseek-coder: When the large language model meets programming–the rise of code intelligence. arXiv preprint arXiv:2401.14196, 2024. find
265. Daya Guo, Dejian Yang, Haowei Zhang, Junxiao Song, Ruoyu Zhang, Runxin Xu, Qihao Zhu, Shirong Ma, Peiyi Wang, Xiao Bi, et al. Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning. arXiv preprint arXiv:2501.12948, 2025.
266. Siyuan Guo, Cheng Deng, Ying Wen, Hechang Chen, Yi Chang, and Jun Wang. Ds-agent: Automated data science by empowering large language models with case-based reasoning. arXiv preprint arXiv:2402.17453, 2024. find
267. Yue Guo, Wei Qiu, Yizhong Wang, and Trevor Cohen. Automated lay language summarization of biomedical scientific reviews. In Proceedings of the AAAI Conference on Artificial Intelligence, volume 35, pages 160–168, May 2021. find
268. Ziyu Guo, Ray Zhang, Hao Chen, Jialin Gao, Dongzhi Jiang, Jiaze Wang, and Pheng-Ann Heng. Sciverse: Unveiling the knowledge comprehension and visual reasoning of lmms on multi-modal scientific problems. arXiv preprint arXiv:2503.10627, 2025. find
269. Rohan Gupta, Devesh Srivastava, Mehar Sahu, Swati Tiwari, Rashmi K Ambasta, and Pravir Kumar. Artificial intelligence to deep learning: machine intelligence approach for drug discovery. Molecular diversity, 25:1315–1360, Apr 2021. find
270. Tarun Gupta and Danish Pruthi. All that glitters is not novel: Plagiarism in ai generated research. arXiv preprint arXiv:2502.16487, 2025. find
271. Anthony GX-Chen, Dongyan Lin, Mandana Samiei, Doina Precup, Blake A Richards, Rob Fergus, and Kenneth Marino. Language agents mirror human causal reasoning biases. how can we help them think like scientists? arXiv preprint arXiv:2505.09614, 2025. — [arXiv:2505.09614](https://arxiv.org/abs/2505.09614) find
272. Hendrik Haarmann. Enhance innovation by boosting idea generation with large language models. INFORMS Journal on Computing, Jul 2025. find
273. Thilo Hagendorff, Sarah Fabi, and Michal Kosinski. Human-like intuitive behavior and reasoning biases emerged in large language models but disappeared in chatgpt. Nature Computational Science, 3(10):833–838, October 2023. ISSN 2662-8457. doi: 10.1038/s43588-023-00527-x. URL http://dx.doi.org/10.103… — [doi:10.1038/s43588-023-00527-x](https://doi.org/10.1038/s43588-023-00527-x) find
274. Lewis Hammond, Alan Chan, Jesse Clifton, Jason Hoelscher-Obermaier, Akbir Khan, Euan McLean, Chandler Smith, Wolfram Barfuss, Jakob Foerster, Tomáš Gavenčiak, et al. Multi-agent risks from advanced ai. arXiv preprint arXiv:2502.14143, 2025. — [arXiv:2502.14143](https://arxiv.org/abs/2502.14143) find
275. Viktor Hangya, Hossain Shaikh Saadi, and Alexander Fraser. Improving low-resource languages in pre-trained multilingual language models. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, pages 11993–12006, Jan 2022. find
276. Matthew G Hanna, Liron Pantanowitz, Brian Jackson, Octavia Palmer, Shyam Visweswaran, Joshua Pantanowitz, Mustafa Deebajah, and Hooman H Rashidi. Ethical and bias considerations in artificial intelligence/machine learning. Modern Pathology, 38(3):100686, Mar 2025. find
277. Qianyue Hao, Jingyang Fan, Fengli Xu, Jian Yuan, and Yong Li. Hlm-cite: Hybrid language model workflow for text-based scientific citation prediction. arXiv preprint arXiv:2410.09112, 2024. — [arXiv:2410.09112](https://arxiv.org/abs/2410.09112) find
278. Shibo Hao, Tianyang Liu, Zhen Wang, and Zhiting Hu. Toolkengpt: Augmenting frozen language models with massive tools via tool embeddings. Advances in Neural Information Processing Systems, 36:45870–45894, Dec 2023.
279. Kenneth D Harris. Airus: a simple workflow for ai-assisted exploration of scientific data. bioRxiv, pages 2025–02, Feb 2025. find
280. Russell Hartley. Efficacy analysis of online artificial intelligence fact-checking tools. The International Review of Information Ethics, 33(1), Apr 2024. find
281. Helia Hashemi, Jason Eisner, Corby Rosset, Benjamin Van Durme, and Chris Kedzie. LLM-rubric: A multidimensional, calibrated approach to automated evaluation of natural language texts. In Lun-Wei Ku, Andre Martins, and Vivek Srikumar, editors, Proceedings of the 62nd Annual Meeting of the Association…
282. Vikas Hassija, Vinay Chamola, Atmesh Mahapatra, Abhinandan Singal, Divyansh Goel, Kaizhu Huang, Simone Scardapane, Indro Spinelli, Mufti Mahmud, and Amir Hussain. Interpreting black-box models: a review on explainable artificial intelligence. Cognitive Computation, 16(1):45–74, Aug 2024. find
283. Kan Hatakeyama-Sato, Toshihiko Nishida, Kenta Kitamura, Yoshitaka Ushiku, Koichi Takahashi, Yuta Nabae, and Teruaki Hayakawa. Perspective on utilizing foundation models for laboratory automation in materials research. arXiv preprint arXiv:2506.12312, 2025. — [arXiv:2506.12312](https://arxiv.org/abs/2506.12312) find
284. Jesse Haworth, Rishi Biswas, Justin Opfermann, Michael Kam, Yaning Wang, Desire Pantalone, Francis X Creighton, Robin Yang, Jin U Kang, and Axel Krieger. Autonomous robotic system with optical coherence tomography guidance for vascular anastomosis. arXiv preprint arXiv:2410.07493, 2024. — [arXiv:2410.07493](https://arxiv.org/abs/2410.07493) find
285. Thomas Hayes, Roshan Rao, Halil Akin, Nicholas J Sofroniew, Deniz Oktay, Zeming Lin, Robert Verkuil, Vincent Q Tran, Jonathan Deaton, Marius Wiggert, et al. Simulating 500 million years of evolution with a language model. Science, page eads0018, Jan 2025. find
286. Kaiyu He and Zhiyu Chen. From reasoning to learning: A survey on hypothesis discovery and rule learning with large language models. arXiv preprint arXiv:2505.21935, 2025. find
287. Yichen He, Guanhua Huang, Peiyuan Feng, Yuan Lin, Yuchen Zhang, Hang Li, et al. Pasa: An llm agent for comprehensive academic paper search. arXiv preprint arXiv:2501.10120, 2025.
288. Tina Heger, Alsayed Algergawy, Marc Brinner, Jonathan M Jeschke, Birgitta König-Ries, Daniel Mietchen, and Sina Zarrieß. Natural language hypotheses in scientific papers and how to tame them: Suggested steps for formalizing complex scientific claims. In Conference on Advances in Robust Argumentation… find
289. Michael V Heinz, Daniel M Mackin, Brianna M Trudeau, Sukanya Bhattacharya, Yinzhou Wang, Haley A Banta, Abi D Jewett, Abigail J Salzhauer, Tess Z Griffin, and Nicholas C Jacobson. Randomized trial of a generative ai chatbot for mental health treatment. Nejm Ai, 2(4):AIoa2400802, Mar 2025. find
290. Sam Henry and Bridget T McInnes. Literature based discovery: models, methods, and trends. Journal of biomedical informatics, 74:20–32, Oct 2017. find
291. Emily Herron, Junqi Yin, and Feiyi Wang. Scitrust: Evaluating the trustworthiness of large language models for science. In SC24-W: Workshops of the International Conference for High Performance Computing, Networking, Storage and Analysis, pages 72–78. IEEE, Nov 2024. find
292. Lukas Hilgert, Danni Liu, and Jan Niehues. Evaluating and training long-context large language models for question answering on scientific papers. In Sachin Kumar, Vidhisha Balachandran, Chan Young Park, Weijia Shi, Shirley Anugrah Hayati, Yulia Tsvetkov, Noah Smith, Hannaneh Hajishirzi, Dongyeop Ka… find
293. Cong Duy Vu Hoang and Min-Yen Kan. Towards automated related work summarization. In Coling 2010: Posters, pages 427–435, Aug 2010. find
294. Michael Peter Hoffmann, Jan Fillies, and Adrian Paschke. Malinowski in the age of ai: Can large language models create a text game based on an anthropological classic? arXiv preprint arXiv:2410.20536, 2024. — [arXiv:2410.20536](https://arxiv.org/abs/2410.20536) find
295. Brendan Hogan, Anmol Kabra, Felipe Siqueira Pacheco, Laura Greenstreet, Joshua Fan, Aaron Ferber, Marta Ummus, Alecsander Brito, Olivia Graham, Lillian Aoki, et al. Aiscivision: A framework for specializing large multimodal models in scientific image classification. arXiv preprint arXiv:2410.21480,… — [arXiv:2410.21480](https://arxiv.org/abs/2410.21480) find
296. Steffen Holter and Mennatallah El-Assady. Deconstructing human-ai collaboration: Agency, interaction, and adaptation. In Computer Graphics forum, volume 43, page e15107. Wiley Online Library, Jun 2024. find
297. Niklas Höpner, Leon Eshuijs, Dimitrios Alivanistos, Giacomo Zamprogno, and Ilaria Tiddi. Automatic evaluation metrics for artificially generated scientific research. arXiv preprint arXiv:2503.05712, 2025. — [arXiv:2503.05712](https://arxiv.org/abs/2503.05712) find
298. Eftekhar Hossain, Sanjeev Kumar Sinha, Naman Bansal, R. Alexander Knipper, Souvika Sarkar, John Salvador, Yash Mahajan, Sri Ram Pavan Kumar Guttikonda, Mousumi Akter, Md. Mahadi Hassan, Matthew Freestone, Matthew C. Williams Jr., Dongji Feng, and Santu Karmaker. LLMs as meta-reviewers’ assistants: A… find
299. Soodeh Hosseini and Hossein Seilani. The role of agentic ai in shaping a smart future: A systematic review. Array, page 100399, Jul 2025. find
300. Jhih-Yi Hsieh. Automated Peer-Reviewer Assignment can be Manipulated to Secure Reviews from Colluders. PhD thesis, Carnegie Mellon University Pittsburgh, PA, May 2024. find
301. Chao-Chun Hsu, Erin Bransom, Jenna Sparks, Bailey Kuehl, Chenhao Tan, David Wadden, Lucy Lu Wang, and Aakanksha Naik. Chime: Llm-assisted hierarchical organization of scientific studies for literature review support. arXiv preprint arXiv:2407.16148, 2024. find
302. Ting-Yao Hsu, Chieh-Yang Huang, Shih-Hong Huang, Ryan Rossi, Sungchul Kim, Tong Yu, C Lee Giles, and Ting-Hao Kenneth Huang. Scicapenter: Supporting caption composition for scientific figures with machine-generated captions and ratings. In Extended Abstracts of the CHI Conference on Human Factors in… find
303. Linmei Hu, Duokang Wang, Yiming Pan, Jifan Yu, Yingxia Shao, Chong Feng, and Liqiang Nie. Novachart: A large-scale dataset towards chart understanding and generation of multimodal large language models. In Proceedings of the 32nd ACM International Conference on Multimedia, pages 3917–3925, Oct 2024.… find
304. Mengkang Hu, Yao Mu, Xinmiao Yu, Mingyu Ding, Shiguang Wu, Wenqi Shao, Qiguang Chen, Bin Wang, Yu Qiao, and Ping Luo. Tree-planner: Efficient close-loop task planning with large language models. arXiv preprint arXiv:2310.08582, 2023. — [arXiv:2310.08582](https://arxiv.org/abs/2310.08582) find
305. Mengkang Hu, Tianxing Chen, Qiguang Chen, Yao Mu, Wenqi Shao, and Ping Luo. Hiagent: Hierarchical working memory management for solving long-horizon agent tasks with large language model. arXiv preprint arXiv:2408.09559, 2024.
306. Mengkang Hu, Tianxing Chen, Yude Zou, Yuheng Lei, Qiguang Chen, Ming Li, Yao Mu, Hongyuan Zhang, Wenqi Shao, and Ping Luo. Text2world: Benchmarking large language models for symbolic world model generation. arXiv preprint arXiv:2502.13092, 2025. find
307. Mengkang Hu, Yuhang Zhou, Wendong Fan, Yuzhou Nie, Bowei Xia, Tao Sun, Ziyu Ye, Zhaoxuan Jin, Yingru Li, Qiguang Chen, et al. Owl: Optimized workforce learning for general multi-agent assistance in real-world task automation. arXiv preprint arXiv:2505.23885, 2025. — [arXiv:2505.23885](https://arxiv.org/abs/2505.23885) find
308. Xiang Hu, Hongyu Fu, Jinge Wang, Yifeng Wang, Zhikun Li, Renjun Xu, Yu Lu, Yaochu Jin, Lili Pan, and Zhenzhong Lan. Nova: An iterative planning and search approach to enhance novelty and diversity of llm generated ideas. arXiv preprint arXiv:2410.14255, 2024. find
309. Xueyu Hu, Ziyu Zhao, Shuang Wei, Ziwei Chai, Qianli Ma, Guoyin Wang, Xuwu Wang, Jing Su, Jingjing Xu, Ming Zhu, et al. Infiagent-dabench: Evaluating agents on data analysis tasks. arXiv preprint arXiv:2401.05507, 2024. — [arXiv:2401.05507](https://arxiv.org/abs/2401.05507) find
310. Yue Hu and Xiaojun Wan. Automatic generation of related work sections in scientific papers: an optimization approach. In Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 1624–1633, Oct 2014. find
311. Yuntong Hu, Zhuofeng Li, Zheng Zhang, Chen Ling, Raasikh Kanjiani, Boxin Zhao, and Liang Zhao. Taxonomy tree generation from citation graph. arXiv preprint arXiv:2410.03761, 2024.
312. Tianyu Hua, Harper Hua, Violet Xiang, Benjamin Klieger, Sang T Truong, Weixin Liang, Fan-Yun Sun, and Nick Haber. Researchcodebench: Benchmarking llms on implementing novel machine learning research code. arXiv preprint arXiv:2506.02314, 2025. find
313. Jiaxin Huang, Shixiang Shane Gu, Le Hou, Yuexin Wu, Xuezhi Wang, Hongkun Yu, and Jiawei Han. Large language models can self-improve. arXiv preprint arXiv:2210.11610, 2022.
314. Jincai Huang, Yongjun Xu, Qi Wang, Qi Cheems Wang, Xingxing Liang, Fei Wang, Zhao Zhang, Wei Wei, Boxuan Zhang, Libo Huang, et al. Foundation models and intelligent decision-making: Progress, challenges, and perspectives. The Innovation, Jun 2025. find
315. Jinyang Huang, Xiachong Feng, Qiguang Chen, Hanjie Zhao, Zihui Cheng, Jiesong Bai, Jingxuan Zhou, Min Li, and Libo Qin. Mldebugging: Towards benchmarking code debugging across multi-library scenarios. arXiv preprint arXiv:2506.13824, 2025. find
316. Kaixuan Huang, Yuanhao Qu, Henry Cousins, William A Johnson, Di Yin, Mihir Shah, Denny Zhou, Russ Altman, Mengdi Wang, and Le Cong. Crispr-gpt: An llm agent for automated design of gene-editing experiments. arXiv preprint arXiv:2404.18021, 2024. find
317. Kexin Huang, Payal Chandak, Qianwen Wang, Shreyas Havaldar, Akhil Vaid, Jure Leskovec, Girish N Nadkarni, Benjamin S Glicksberg, Nils Gehlenborg, and Marinka Zitnik. A foundation model for clinician-centered drug repurposing. Nature Medicine, 30(12):3601–3613, Sep 2024. find
318. Kexin Huang, Serena Zhang, Hanchen Wang, Yuanhao Qu, Yingzhou Lu, Yusuf Roohani, Ryan Li, Lin Qiu, Junze Zhang, Yin Di, et al. Biomni: A general-purpose biomedical ai agent. bioRxiv, pages 2025–05, Jun 2025. find
319. Lei Huang, Weijiang Yu, Weitao Ma, Weihong Zhong, Zhangyin Feng, Haotian Wang, Qianglong Chen, Weihua Peng, Xiaocheng Feng, Bing Qin, et al. A survey on hallucination in large language models: Principles, taxonomy, challenges, and open questions. ACM Transactions on Information Systems, 43 (2):1–55,…
320. Lifu Huang, Danai Koutra, Adithya Kulkarni, Temiloluwa Prioleau, Qingyun Wu, Yujun Yan, Yaoqing Yang, James Zou, and Dawei Zhou. Towards agentic ai for science: Hypothesis generation, comprehension, quantification, and validation. In Companion Proceedings of the ACM on Web Conference 2025, pages 163… find
321. Muye Huang, Lingling Zhang, Jie Ma, Han Lai, Fangzhi Xu, Yifei Li, Wenjun Wu, Yaqiang Wu, and Jun Liu. Chartsketcher: Reasoning with multimodal feedback and reflection for chart understanding. arXiv preprint arXiv:2505.19076, 2025. — [arXiv:2505.19076](https://arxiv.org/abs/2505.19076) find
322. Qian Huang, Jian Vora, Percy Liang, and Jure Leskovec. Mlagentbench: Evaluating language agents on machine learning experimentation. arXiv preprint arXiv:2310.03302, 2023.
323. Shengzhi Huang, Qicong Wang, Wei Lu, Lingyu Liu, Zhenzhen Xu, and Yong Huang. Papereval: A universal, quantitative, and explainable paper evaluation method powered by a multi-agent system. Information Processing & Management, 62(6):104225, Nov 2025. find
324. Xiang Huang, CY Zhao, Hong Wang, and Shenghong Ju. Ai-assisted inverse design of sequence-ordered high intrinsic thermal conductivity polymers. Materials Today Physics, 44:101438, May 2024. find
325. Yinya Huang, Xiaohan Lin, Zhengying Liu, Qingxing Cao, Huajian Xin, Haiming Wang, Zhenguo Li, Linqi Song, and Xiaodan Liang. Mustard: Mastering uniform synthesis of theorem and proof data. arXiv preprint arXiv:2402.08957, 2024. find
326. Yizhe Huang, Xingbo Wang, Hao Liu, Fanqi Kong, Aoyang Qin, Min Tang, Xiaoxi Wang, Song-Chun Zhu, Mingjie Bi, Siyuan Qi, et al. Adasociety: An adaptive environment with social structures for multi-agent decision-making. arXiv preprint arXiv:2411.03865, 2024. — [arXiv:2411.03865](https://arxiv.org/abs/2411.03865) find
327. B Ian Hutchins, Xin Yuan, James M Anderson, and George M Santangelo. Relative citation ratio (rcr): a new metric that uses citation rates to measure influence at the article level. PLoS biology, 14(9): e1002541, Sep 2016. find
328. Holland Hysmith, Elham Foadian, Shakti P Padhy, Sergei V Kalinin, Rob G Moore, Olga S Ovchinnikova, and Mahshid Ahmadi. The future of self-driving laboratories: from human in the loop interactive ai to gamification. Digital Discovery, 3(4):621–636, Mar 2024. find
329. Maximilian Idahl and Zahra Ahmadi. Openreviewer: A specialized large language model for generating critical scientific paper reviews. arXiv preprint arXiv:2412.11948, 2024. find
330. Tal Ifargan, Lukas Hafner, Maor Kern, Ori Alcalay, and Roy Kishony. Autonomous llm-driven research—from data to human-verifiable research papers. NEJM AI, 2(1):AIoa2400555, Dec 2025. find
331. Hayato Ikoma and Teruko Mitamura. Can ai examine novelty of patents?: Novelty evaluation based on the correspondence between patent claim and prior art. arXiv preprint arXiv:2502.06316, 2025. — [arXiv:2502.06316](https://arxiv.org/abs/2502.06316) find
332. Autoscience Institute. Carl technical report, Mar 2025. URL https://drive.google.com/file/ d/1iVedOdZDuEdjS4lcm9Z7i8oEDGWfzVJq/view. Carl Technical Report. ↗
333. Amazon Artificial General Intelligence. The amazon nova family of models: Technical report and model card. Jun 2025. find
334. Mete Ismayilzada, Debjit Paul, Antoine Bosselut, and Lonneke van der Plas. Creativity in ai: Progresses and challenges. arXiv preprint arXiv:2410.17218, 2024. — [arXiv:2410.17218](https://arxiv.org/abs/2410.17218) find
335. Takumi Ito, Tatsuki Kuribayashi, Hayato Kobayashi, Ana Brassard, Masato Hagiwara, Jun Suzuki, and Kentaro Inui. Diamonds in the rough: Generating fluent sentences from early-stage drafts for academic writing assistance. arXiv preprint arXiv:1910.09180, 2019. find
336. Aaron Jaech, Adam Kalai, Adam Lerer, Adam Richardson, Ahmed El-Kishky, Aiden Low, Alec Helyar, Aleksander Madry, Alex Beutel, Alex Carney, et al. Openai o1 system card. arXiv preprint arXiv:2412.16720, 2024.
337. Nazanin Jafari and James Allan. Robust claim verification through fact detection. arXiv preprint arXiv:2407.18367, 2024. — [arXiv:2407.18367](https://arxiv.org/abs/2407.18367) find
338. Peter Jansen, Marc-Alexandre Côté, Tushar Khot, Erin Bransom, Bhavana Dalvi Mishra, Bodhisattwa Prasad Majumder, Oyvind Tafjord, and Peter Clark. Discoveryworld: A virtual environment for developing and evaluating automated scientific discovery agents. Advances in Neural Information Processing Syste… find
339. Rasika Jayarathna, Thossaporn Onsree, Samuel Drummond, Jennifer Naglic, and Jochen Lauterbach. Experimental discovery of novel ammonia synthesis catalysts via active learning. Journal of Materials Chemistry A, 12(5):3046–3060, Feb 2024. find
340. Deyi Ji, Lanyun Zhu, Siqi Gao, Peng Xu, Hongtao Lu, Jieping Ye, and Feng Zhao. Tree-of-table: Unleashing the power of llms for enhanced large-scale table understanding. arXiv preprint arXiv:2411.08516, 2024. — [arXiv:2411.08516](https://arxiv.org/abs/2411.08516) find
341. Qinjin Jia, Jialin Cui, Yunkai Xiao, Chengyuan Liu, Parvez Rashid, and Edward Gehringer. All-in-one: Multi-task learning bert models for evaluating peer assessments. International Educational Data Mining Society, Oct 2021. find
342. Albert Q Jiang, Sean Welleck, Jin Peng Zhou, Wenda Li, Jiacheng Liu, Mateja Jamnik, Timothée Lacroix, Yuhuai Wu, and Guillaume Lample. Draft, sketch, and prove: Guiding formal theorem provers with informal proofs. arXiv preprint arXiv:2210.12283, 2022.
343. Albert Qiaochu Jiang, Wenda Li, Szymon Tworkowski, Konrad Czechowski, Tomasz Odrzygóźdź, Piotr Miłoś, Yuhuai Wu, and Mateja Jamnik. Thor: Wielding hammers to integrate language models and automated theorem provers. Advances in Neural Information Processing Systems, 35:8360–8373, Nov 2022. find
344. Fengqing Jiang. Identifying and mitigating vulnerabilities in llm-integrated applications. Master’s thesis, University of Washington, Jul 2024. find
345. Nan Jiang, Shanchao Liang, Chengxiao Wang, Jiannan Wang, and Lin Tan. Latte: Improving latex recognition for tables and formulae with iterative refinement. In Proceedings of the AAAI Conference on Artificial Intelligence, volume 39, pages 4030–4038, Apr 2025. find
346. Xiaowei Jiang, Liang Ou, Yanan Chen, Na Ao, Yu-Cheng Chang, Thomas Do, and Chin-Teng Lin. A fuzzy logic-based approach to predict human interaction by functional near-infrared spectroscopy. IEEE Transactions on Fuzzy Systems, Jan 2025. find
347. Xue Jiang, Dezhen Xue, William Yi Wang, Jianjun Liu, Mingli Yang, Yanjing Su, et al. Ai4materials: Transforming the landscape of materials science and enigneering. Review of Materials Research, page 100010, Jan 2025. find
348. Licheng Jiao, Xue Song, Chao You, Xu Liu, Lingling Li, Puhua Chen, Xu Tang, Zhixi Feng, Fang Liu, Yuwei Guo, et al. Ai meets physics: a comprehensive survey. Artificial Intelligence Review, 57(9):256, Aug 2024. find
349. Carlos E Jimenez, John Yang, Alexander Wettig, Shunyu Yao, Kexin Pei, Ofir Press, and Karthik R Narasimhan. SWE-bench: Can language models resolve real-world github issues? In The Twelfth International Conference on Learning Representations, Jan 2024. URL https://openreview.net/ forum?id=VTF8yNQM66. ↗
350. Qiao Jin, Bhuwan Dhingra, Zhengping Liu, William W Cohen, and Xinghua Lu. Pubmedqa: A dataset for biomedical research question answering. arXiv preprint arXiv:1909.06146, 2019.
351. Yiqiao Jin, Qinlin Zhao, Yiyang Wang, Hao Chen, Kaijie Zhu, Yijia Xiao, and Jindong Wang. Agentreview: Exploring peer review dynamics with llm agents. arXiv preprint arXiv:2406.12708, 2024. find
352. Liqiang Jing, Zhehui Huang, Xiaoyang Wang, Wenlin Yao, Wenhao Yu, Kaixin Ma, Hongming Zhang, Xinya Du, and Dong Yu. Dsbench: How far are data science agents to becoming data science experts? arXiv preprint arXiv:2409.07703, 2024. find
353. Wayne Johnson and Devon Proudfoot. Greater variability in judgements of the value of novel ideas. Nature Human Behaviour, 8(3):471–479, Jan 2024. find
354. Cameron R Jones and Benjamin K Bergen. Large language models pass the turing test. arXiv preprint arXiv:2503.23674, 2025. — [arXiv:2503.23674](https://arxiv.org/abs/2503.23674) find
355. John Jumper, Richard Evans, Alexander Pritzel, Tim Green, Michael Figurnov, Olaf Ronneberger, Kathryn Tunyasuvunakool, Russ Bates, Augustin Žídek, Anna Potapenko, et al. Highly accurate protein structure prediction with alphafold. nature, 596(7873):583–589, Jul 2021.
356. Prerna Juneja and Tanushree Mitra. Human and technological infrastructures of fact-checking. Proceedings of the ACM on Human-Computer Interaction, 6(CSCW2):1–36, Nov 2022. find
357. Rebecca E Kaiser, Farshad Sadr, Trevor Yuen, Till Krenz, Lee Chin-Chin, C Dominguez Sheela, Daru LL Ransford, and Erin Kobetz. 376 using a large language model to create lay summaries of clinical study descriptions. Journal of Clinical and Translational Science, 9(s1):116–116, Apr 2025. find
358. Dmitry Kalashnikov, Alex Irpan, Peter Pastor, Julian Ibarz, Alexander Herzog, Eric Jang, Deirdre Quillen, Ethan Holly, Mrinal Kalakrishnan, Vincent Vanhoucke, et al. Scalable deep reinforcement learning for vision-based robotic manipulation. In Conference on robot learning, pages 651–673. PMLR, Oct… find
359. Subbarao Kambhampati, Karthik Valmeekam, Lin Guan, Mudit Verma, Kaya Stechly, Siddhant Bhambri, Lucas Paul Saldyt, and Anil B Murthy. Position: Llms can’t plan, but can help planning in llm-modulo frameworks. In Forty-first International Conference on Machine Learning, May 2024. find
360. Dongyeop Kang, Waleed Ammar, Bhavana Dalvi, Madeleine van Zuylen, Sebastian Kohlmeier, Eduard Hovy, and Roy Schwartz. A dataset of peer reviews (peerread): Collection, insights and nlp applications. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computatio…
361. Hyeonsu B Kang, Rafal Kocielnik, Andrew Head, Jiangjiang Yang, Matt Latzke, Aniket Kittur, Daniel S Weld, Doug Downey, and Jonathan Bragg. From who you know to what you read: Augmenting scientific recommendations with implicit social networks. In Proceedings of the 2022 CHI Conference on Human Facto… find
362. Hyeonsu B Kang, Nouran Soliman, Matt Latzke, Joseph Chee Chang, and Jonathan Bragg. Comlittee: Literature discovery with personal elected author committees. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, pages 1–20, Apr 2023. find
363. Sungmin Kang, Bei Chen, Shin Yoo, and Jian-Guang Lou. Explainable automated debugging via large language model-driven scientific debugging. Empirical Software Engineering, 30(2):1–28, Mar 2025. find
364. Chia Hsiang Kao, Wenting Zhao, Shreelekha Revankar, Samuel Speas, Snehal Bhagat, Rajeev Datta, Cheng Perng Phoo, Utkarsh Mall, Carl Vondrick, Kavita Bala, et al. Towards llm agents for earth observation. arXiv preprint arXiv:2504.12110, 2025. find
365. Wei-Yu Kao and An-Zi Yen. Magic: Multi-argument generation with self-refinement for domain generalization in automatic fact-checking. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 10891– 10902, May… find
366. Maryna Kapitonova and Tonio Ball. Human-ai teaming using large language models: Boosting brain-computer interfacing (bci) and brain research. arXiv preprint arXiv:2501.01451, 2024. — [arXiv:2501.01451](https://arxiv.org/abs/2501.01451) find
367. Andres Karjus. Machine-assisted quantitizing designs: augmenting humanities and social sciences with artificial intelligence. Humanities and Social Sciences Communications, 12(1):1–18, Feb 2025. find
368. Tetsu Kasanishi, Masaru Isonuma, Junichiro Mori, and Ichiro Sakata. Scireviewgen: a large-scale dataset for automatic literature review generation. arXiv preprint arXiv:2305.15186, 2023. find
369. Uri Katz, Mosh Levy, and Yoav Goldberg. Knowledge navigator: Llm-guided browsing framework for exploratory search in scientific literature. arXiv preprint arXiv:2408.15836, 2024. find
370. Nan Rosemary Ke, Danny P Sawyer, Hubert Soyer, Martin Engelcke, David P Reichert, Drew A Hudson, John Reid, Alexander Lerchner, Danilo Jimenez Rezende, Timothy P Lillicrap, et al. Can foundation models actively gather information in interactive environments to test hypotheses? arXiv preprint arXiv:2… — [arXiv:2412.06438](https://arxiv.org/abs/2412.06438) find
371. Martin Kerwer, Anita Chasiotis, Johannes Stricker, Armin Günther, and Tom Rosman. Straight from the scientist’s mouth—plain language summaries promote laypeople’s comprehension and knowledge acquisition when reading about individual research findings in psychology. Collabra: Psychology, 7 (1), Feb 2… find
372. Farhana Keya, Gollam Rabby, Prasenjit Mitra, Sahar Vahdati, Sören Auer, and Yaser Jaradeh. Sci-idea: Context-aware scientific ideation using token and sentence embeddings. arXiv preprint arXiv:2503.19257, 2025.
373. Mohamed Khalifa and Mona Albadawy. Using artificial intelligence in academic writing and research: An essential productivity tool. Computer Methods and Programs in Biomedicine Update, page 100145, Mar 2024. find
374. Mohamed Khalifa, Mona Albadawy, and Usman Iqbal. Advancing clinical decision support: The role of artificial intelligence across six domains. Computer Methods and Programs in Biomedicine Update, 5: 100142, Feb 2024. find
375. Wasif Khan, Seowung Leem, Kyle B See, Joshua K Wong, Shaoting Zhang, and Ruogu Fang. A comprehensive survey of foundation models in medicine. IEEE Reviews in Biomedical Engineering, Jan 2025. find
376. Jaeho Kim, Yunseok Lee, and Seulki Lee. Position: The ai conference peer review crisis demands author feedback and reviewer rewards. arXiv preprint arXiv:2505.04966, 2025. find
377. Jaeyoung Kim, Jongho Lee, Hong-Jun Choi, Ting-Yao Hsu, Chieh-Yang Huang, Sungchul Kim, Ryan Rossi, Tong Yu, Clyde Lee Giles, Ting-Hao’Kenneth’ Huang, et al. Multi-llm collaborative caption generation in scientific documents. arXiv preprint arXiv:2501.02552, 2025. — [arXiv:2501.02552](https://arxiv.org/abs/2501.02552) find
378. Jiho Kim, Sungjin Park, Yeonsu Kwon, Yohan Jo, James Thorne, and Edward Choi. Factkg: Fact verification via reasoning on knowledge graphs. arXiv preprint arXiv:2305.06590, 2023. find
379. Min-Woo Kim, Hyo-Bin Park, Hee-Jin Ahn, Woo-Ram Park, Jae-Wan Jeon, Kyong-Ha Lee, Ryong Lee, and Dong-Geol Choi. Autopaperbench: An mllm-based framework for automatic generation of paper understanding evaluation benchmarks. Electronics, 14(6):1175, Mar 2025. find
380. Seonok Kim. Medbiolm: Optimizing medical and biological qa with fine-tuned large language models and retrieval-augmented generation. arXiv preprint arXiv:2502.03004, 2025. — [arXiv:2502.03004](https://arxiv.org/abs/2502.03004) find
381. Ross D King, Kenneth E Whelan, Ffion M Jones, Philip GK Reiser, Christopher H Bryant, Stephen H Muggleton, Douglas B Kell, and Stephen G Oliver. Functional genomic hypothesis generation and experimentation by a robot scientist. Nature, 427(6971):247–252, Jan 2004. find
382. Chhavi Kirtani, Madhav Krishan Garg, Tejash Prasad, Tanmay Singhal, Murari Mandal, and Dhruv Kumar. Revieweval: An evaluation framework for ai-generated reviews. arXiv preprint arXiv:2502.11736, 2025. find
383. Stephen T Knox, Kai E Wu, Nazrul Islam, Roisin O’Connell, Peter M Pittaway, Kudakwashe E Chingono, John Oyekan, George Panoutsos, Thomas W Chamberlain, Richard A Bourne, et al. Self-driving laboratory platform for many-objective self-optimisation of polymer nanoparticle synthesis with cloud-integrat… find
384. Patrick Tser Jern Kon, Jiachen Liu, Qiuyi Ding, Yiming Qiu, Zhenning Yang, Yibo Huang, Jayanth Srinivasa, Myungjin Lee, Mosharaf Chowdhury, and Ang Chen. Curie: Toward rigorous and automated scientific experimentation with ai agents. arXiv preprint arXiv:2502.16069, 2025. find
385. Patrick Tser Jern Kon, Jiachen Liu, Xinyi Zhu, Qiuyi Ding, Jingjia Peng, Jiarong Xing, Yibo Huang, Yiming Qiu, Jayanth Srinivasa, Myungjin Lee, et al. Exp-bench: Can ai conduct ai research experiments? arXiv preprint arXiv:2505.24785, 2025. find
386. Kayvan Kousha and Mike Thelwall. Artificial intelligence to support publishing and peer review: A summary and review. Learned Publishing, 37(1):4–12, Aug 2024. find
387. Mario Krenn, Lorenzo Buffoni, Bruno Coutinho, Sagi Eppel, Jacob Gates Foster, Andrew Gritsevskiy, Harlin Lee, Yichao Lu, Joao P Moutinho, Nima Sanjabi, et al. Predicting the future of ai with ai: High-quality link prediction in an exponentially growing knowledge network. arXiv preprint arXiv:2210.00… — [arXiv:2210.00881](https://arxiv.org/abs/2210.00881) find
388. Christin Katharina Kreutz and Ralf Schenkel. Scientific paper recommendation systems: a literature review of recent publications. International journal on digital libraries, 23(4):335–369, Oct 2022. find
389. Amrith Krishna, Sebastian Riedel, and Andreas Vlachos. Proofver: Natural logic theorem proving for fact verification. Transactions of the Association for Computational Linguistics, 10:1013–1030, Sep 2022. find
390. Agustinus Kristiadi, Felix Strieth-Kalthoff, Marta Skreta, Pascal Poupart, Alán Aspuru-Guzik, and Geoff Pleiss. A sober look at llms for material discovery: Are they actually good for bayesian optimization over molecules? arXiv preprint arXiv:2402.05015, 2024. — [arXiv:2402.05015](https://arxiv.org/abs/2402.05015) find
391. Anastasia Krithara, Anastasios Nentidis, Konstantinos Bougiatiotis, and Georgios Paliouras. Bioasq-qa: A manually curated corpus for biomedical question answering. Scientific Data, 10(1):170, Mar 2023. find
392. Max Ku, Thomas Chong, Jonathan Leung, Krish Shah, Alvin Yu, and Wenhu Chen. Theoremexplaina-gent: Towards video-based multimodal explanations for llm theorem understanding. arXiv preprint arXiv:2502.19400, 2025. — [arXiv:2502.19400](https://arxiv.org/abs/2502.19400) find
393. Lorenz Kuhn, Yarin Gal, and Sebastian Farquhar. Clam: Selective clarification for ambiguous questions with generative language models. arXiv preprint arXiv:2212.07769, 2022. find
394. Adithya Kulkarni, Fatimah Alotaibi, Xinyue Zeng, Longfeng Wu, Tong Zeng, Barry Menglong Yao, Minqian Liu, Shuaicheng Zhang, Lifu Huang, and Dawei Zhou. Scientific hypothesis generation and validation: Methods, datasets, and future directions. arXiv preprint arXiv:2505.04651, 2025. find
395. Asheesh Kumar, Tirthankar Ghosal, Saprativa Bhattacharjee, and Asif Ekbal. Towards automated meta-review generation via an nlp/ml pipeline in different stages of the scholarly peer review process. International Journal on Digital Libraries, 25(3):493–504, Apr 2024. find
396. Harsh Kumar, Jonathan Vincentius, Ewan Jordan, and Ashton Anderson. Human creativity in the age of llms: Randomized experiments on divergent and convergent thinking. In Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems, pages 1–18, Apr 2025. find
397. Sandeep Kumar, Tirthankar Ghosal, and Asif Ekbal. When reviewers lock horn: Finding disagreement in scientific peer reviews. arXiv preprint arXiv:2310.18685, 2023. — [arXiv:2310.18685](https://arxiv.org/abs/2310.18685) find
398. Sandeep Kumar, Tirthankar Ghosal, Vinayak Goyal, and Asif Ekbal. Can large language models unlock novel scientific research ideas? arXiv preprint arXiv:2409.06185, 2024.
399. Sujit Kumar, Anshul Sharma, Siddharth Hemant Khincha, Gargi Shroff, Sanasam Ranbir Singh, and Rahul Mishra. Sciclaimhunt: A large dataset for evidence-based scientific claim verification. arXiv preprint arXiv:2502.10003, 2025. — [arXiv:2502.10003](https://arxiv.org/abs/2502.10003) find
400. Tsung-Ting Kuo, Rodney A Gabriel, Jejo Koola, Robert T Schooley, and Lucila Ohno-Machado. Distributed cross-learning for equitable federated models-privacy-preserving prediction on data from five california hospitals. Nature Communications, 16(1):1371, Feb 2025. find
401. Ilia Kuznetsov, Osama Mohammed Afzal, Koen Dercksen, Nils Dycke, Alexander Goldberg, Tom Hope, Dirk Hovy, Jonathan K Kummerfeld, Anne Lauscher, Kevin Leyton-Brown, et al. What can natural language processing do for peer review? arXiv preprint arXiv:2405.06563, 2024. find
402. J Kvapil, G Borca-Tasciuc, H Bossi, K Chen, Y Chen, Y Corrales Morales, H Da Costa, C Da Silva, C Dean, J Durham, et al. Intelligent experiments through real-time ai: Fast data processing and autonomous detector control for sphenix and future eic detectors. arXiv preprint arXiv:2501.04845, 2025. — [arXiv:2501.04845](https://arxiv.org/abs/2501.04845) find
403. Daeun Kyung, Hyunseung Chung, Seongsu Bae, Jiho Kim, Jae Ho Sohn, Taerim Kim, Soo Kyung Kim, and Edward Choi. Patientsim: A persona-driven simulator for realistic doctor-patient interactions. arXiv preprint arXiv:2505.17818, 2025. — [arXiv:2505.17818](https://arxiv.org/abs/2505.17818) find
404. Arash Lagzian, Srinivas Anumasa, and Dianbo Liu. Multi-novelty: Improve the diversity and novelty of contents generated by large language models via inference-time multi-views brainstorming. arXiv preprint arXiv:2502.12700, 2025. — [arXiv:2502.12700](https://arxiv.org/abs/2502.12700) find
405. Yuxuan Lai, Yupeng Wu, Yidan Wang, Wenpeng Hu, and Chen Zheng. Instruct large language models to generate scientific literature survey step by step. In CCF International Conference on Natural Language Processing and Chinese Computing, pages 484–496. Springer, Nov 2024. find
406. Zheyuan Lai and Yingming Pu. Prim: Principle-inspired material discovery through multi-agent collaboration. arXiv preprint arXiv:2504.08810, 2025. — [arXiv:2504.08810](https://arxiv.org/abs/2504.08810) find
407. Jakub Lála, Odhran O’Donoghue, Aleksandar Shtedritski, Sam Cox, Samuel G Rodriques, and Andrew D White. Paperqa: Retrieval-augmented generative agent for scientific research. arXiv preprint arXiv:2312.07559, 2023. find
408. Hilbert Yuen In Lam, Xing Er Ong, and Marek Mutwil. Large language models in plant biology. Trends in Plant Science, Oct 2024. find
409. Guillaume Lample, Timothee Lacroix, Marie-Anne Lachaux, Aurelien Rodriguez, Amaury Hayat, Thibaut Lavril, Gabriel Ebner, and Xavier Martinet. Hypertree proof search for neural theorem proving. Advances in Neural Information Processing Systems, 35:26337–26349, Nov 2022.
410. Ge Lan, Mengting Hu, Ye Li, and Yuzhi Zhang. Contrastive knowledge integrated graph neural networks for chinese medical text classification. Engineering Applications of Artificial Intelligence, 122: 106057, Jun 2023. find
411. Wuyang Lan, Wenzheng Wang, Changwei Ji, Guoxing Yang, Yongbo Zhang, Xiaohong Liu, Song Wu, and Guangyu Wang. Clinicalgpt-r1: Pushing reasoning capability of generalist disease diagnosis with large language model. arXiv preprint arXiv:2504.09421, 2025. — [arXiv:2504.09421](https://arxiv.org/abs/2504.09421) find
412. Zhiqian Lan, Yuxuan Jiang, Ruiqi Wang, Xuanbing Xie, Rongkui Zhang, Yicheng Zhu, Peihang Li, Tianshuo Yang, Tianxing Chen, Haoyu Gao, et al. Autobio: A simulation and benchmark for robotic automation in digital biology laboratory. arXiv preprint arXiv:2505.14030, 2025. — [arXiv:2505.14030](https://arxiv.org/abs/2505.14030) find
413. Robert Tjarko Lange, Aaditya Prasad, Qi Sun, Maxence Faldor, Yujin Tang, and David Ha. The ai cuda engineer: Agentic cuda kernel discovery, optimization and composition. Technical report, Technical report, Sakana AI, 02 2025, Feb 2025. find
414. Antonio Laverghetta Jr, Tuhin Chakrabarty, Tom Hope, Jimmy Pronchick, Krupa Bhawsar, and Roger E Beaty. How do humans and language models reason about creativity? a comparative analysis. arXiv preprint arXiv:2502.03253, 2025. — [arXiv:2502.03253](https://arxiv.org/abs/2502.03253) find
415. Nam Le Hai, Dung Manh Nguyen, and Nghi DQ Bui. Repoexec: Evaluate code generation with a repository-level executable benchmark. arXiv e-prints, pages arXiv–2406, 2024. find
416. Jingoo Lee, Kyungho Lim, Young-Chul Jung, and Byung-Hoon Kim. Psyche: A multi-faceted patient simulation framework for evaluation of psychiatric assessment conversational agents. arXiv preprint arXiv:2501.01594, 2025. — [arXiv:2501.01594](https://arxiv.org/abs/2501.01594) find
417. Jisoo Lee, Jieun Lee, and Jeong-Ju Yoo. The role of large language models in the peer-review process: opportunities and challenges for medical journal reviewers and editors. Journal of Educational Evaluation for Health Professions, 22, Jan 2025. find
418. Mina Lee, Percy Liang, and Qian Yang. Coauthor: Designing a human-ai collaborative writing dataset for exploring language model capabilities. In Proceedings of the 2022 CHI conference on human factors in computing systems, pages 1–19, Apr 2022. find
419. Namkyeong Lee, Edward De Brouwer, Ehsan Hajiramezanali, Tommaso Biancalani, Chanyoung Park, and Gabriele Scalia. Rag-enhanced collaborative llm agents for drug discovery. arXiv preprint arXiv:2502.17506, 2025. — [arXiv:2502.17506](https://arxiv.org/abs/2502.17506) find
420. Seungyeon Lee, Ruoqi Liu, Feixiong Cheng, and Ping Zhang. A deep subgrouping framework for precision drug repurposing via emulating clinical trials on real-world patient data. arXiv preprint arXiv:2412.20373, 2024. — [arXiv:2412.20373](https://arxiv.org/abs/2412.20373) find
421. Suk Ki Lee and Hyunwoong Ko. Generative machine learning in adaptive control of dynamic manufacturing processes: A review. arXiv preprint arXiv:2505.00210, 2025. — [arXiv:2505.00210](https://arxiv.org/abs/2505.00210) find
422. Yoonjoo Lee, Hyeonsu B Kang, Matt Latzke, Juho Kim, Jonathan Bragg, Joseph Chee Chang, and Pao Siangliulue. Paperweaver: Enriching topical paper alerts by contextualizing recommended papers with user-collected papers. In Proceedings of the 2024 CHI Conference on Human Factors in Computing Systems, p… find
423. Steven A Lehr, Aylin Caliskan, Suneragiri Liyanage, and Mahzarin R Banaji. Chatgpt as research scientist: probing gpt’s capabilities as a research librarian, research ethicist, data generator, and data predictor. Proceedings of the National Academy of Sciences, 121(35):e2404328121, Jul 2024. find
424. Yan Leng, Yi Zhong, Zhi Gu, Peiyi Li, Haoting Cui, Xing Li, Yang Liu, and Jiayu Wan. Intelligent, personalized scientific assistant via large language models for solid-state battery research. ACS Materials Letters, 7(5):1807–1816, Apr 2025. find
425. Shi Xuan Leong, Sergio Pablo-García, Brandon Wong, and Alán Aspuru-Guzik. Mermaid: Universal multimodal mining of chemical reactions from pdfs using vision-language models. Mar 2025. find
426. Sergey Levine, Chelsea Finn, Trevor Darrell, and Pieter Abbeel. End-to-end training of deep visuomotor policies. Journal of Machine Learning Research, 17(39):1–40, Apr 2016. find
427. Sergey Levine, Peter Pastor, Alex Krizhevsky, Julian Ibarz, and Deirdre Quillen. Learning hand-eye coordination for robotic grasping with deep learning and large-scale data collection. The International journal of robotics research, 37(4-5):421–436, Jun 2018. find
428. Kevin Leyton-Brown, Yatin Nandwani, Hedayat Zarkoob, Chris Cameron, Neil Newman, Dinesh Raghu, et al. Matching papers and reviewers at large conferences. Artificial Intelligence, 331:104119, Jun 2024. find
429. Bohan Li, Jiannan Guan, Longxu Dou, Yunlong Feng, Dingzirui Wang, Yang Xu, Enbo Wang, Qiguang Chen, Bichen Wang, Xiao Xu, et al. Can large language models understand you better? an mbti personality detection dataset aligned with population traits. arXiv preprint arXiv:2412.12510, 2024. find
430. Chuhan Li, Ziyao Shangguan, Yilun Zhao, Deyuan Li, Yixin Liu, and Arman Cohan. M3SciQA: A multi-modal multi-document scientific QA benchmark for evaluating foundation models. In Yaser Al-Onaizan, Mohit Bansal, and Yun-Nung Chen, editors, Findings of the Association for Computational Linguistics: EMN… find
431. Junkai Li, Yunghwei Lai, Weitao Li, Jingyi Ren, Meng Zhang, Xinhui Kang, Siyu Wang, Peng Li, Ya-Qin Zhang, Weizhi Ma, et al. Agent hospital: A simulacrum of hospital with evolvable medical agents. arXiv preprint arXiv:2405.02957, 2024. — [arXiv:2405.02957](https://arxiv.org/abs/2405.02957) find
432. Kun Li, Zhennan Wu, Shoupeng Wang, and Wenbin Hu. Drugpilot: Llm-based parameterized reasoning agent for drug discovery. arXiv preprint arXiv:2505.13940, 2025. — [arXiv:2505.13940](https://arxiv.org/abs/2505.13940) find
433. Lei Li, Yuqi Wang, Runxin Xu, Peiyi Wang, Xiachong Feng, Lingpeng Kong, and Qi Liu. Multimodal ArXiv: A dataset for improving scientific comprehension of large vision-language models. In Lun-Wei Ku, Andre Martins, and Vivek Srikumar, editors, Proceedings of the 62nd Annual Meeting of the Association…
434. Li Li, Yuxi Fan, Mike Tse, and Kuo-Yi Lin. A review of applications in federated learning. Computers & Industrial Engineering, 149:106854, Nov 2020. find
435. Long Li, Weiwen Xu, Jiayan Guo, Ruochen Zhao, Xingxuan Li, Yuqian Yuan, Boqiang Zhang, Yuming Jiang, Yifei Xin, Ronghao Dang, et al. Chain of ideas: Revolutionizing research via novel idea development with llm agents. arXiv preprint arXiv:2410.13185, 2024. find
436. Miao Li, Eduard Hovy, and Jey Han Lau. Summarizing multiple documents with conversational structure for meta-review generation. arXiv preprint arXiv:2305.01498, 2023. find
437. Miao Li, Jey Han Lau, and Eduard Hovy. A sentiment consolidation framework for meta-review generation. arXiv preprint arXiv:2402.18005, 2024. find
438. Raymond Li, Loubna Ben Allal, Yangtian Zi, Niklas Muennighoff, Denis Kocetkov, Chenghao Mou, Marc Marone, Christopher Akiki, Jia Li, Jenny Chim, et al. Starcoder: may the source be with you! arXiv preprint arXiv:2305.06161, 2023. find
439. Ruifeng Li, Dongzhan Zhou, Ancheng Shen, Ao Zhang, Mao Su, Mingqian Li, Hongyang Chen, Gang Chen, Yin Zhang, Shufei Zhang, et al. Physical formula enhanced multi-task learning for pharmacokinetics prediction. arXiv preprint arXiv:2404.10354, 2024. — [arXiv:2404.10354](https://arxiv.org/abs/2404.10354) find
440. Ruifeng Li, Mingqian Li, Wei Liu, Yuhua Zhou, Xiangxin Zhou, Yuan Yao, Qiang Zhang, and Hongyang Chen. Unimatch: Universal matching from atom to task for few-shot drug discovery. arXiv preprint arXiv:2502.12453, 2025. — [arXiv:2502.12453](https://arxiv.org/abs/2502.12453) find
441. Ruikun Li, Yan Lu, Shixiang Tang, Biqing Qi, and Wanli Ouyang. Mllm-based discovery of intrinsic coordinates and governing equations from high-dimensional data. arXiv preprint arXiv:2505.11940, 2025. — [arXiv:2505.11940](https://arxiv.org/abs/2505.11940) find
442. Ruochen Li, Liqiang Jing, Chi Han, Jiawei Zhou, and Xinya Du. Learning to generate research idea with dynamic control. arXiv preprint arXiv:2412.14626, 2024. — [arXiv:2412.14626](https://arxiv.org/abs/2412.14626) find
443. Ruochen Li, Teerth Patel, Qingyun Wang, and Xinya Du. Mlr-copilot: Autonomous machine learning research based on large language models agents. arXiv preprint arXiv:2408.14033, 2024. find
444. Ruosen Li, Ruochen Li, Barry Wang, and Xinya Du. Iqa-eval: Automatic evaluation of human-model interactive question answering. Advances in Neural Information Processing Systems, 37:109894–109921, Dec 2024. find
445. Sitong Li, Stefano Padilla, Pierre Le Bras, Junyu Dong, and Mike Chantler. A review of llm-assisted ideation. arXiv preprint arXiv:2503.00946, 2025. — [arXiv:2503.00946](https://arxiv.org/abs/2503.00946) find
446. Wenyu Li, Zhitao Mao, Zhengyang Xiao, Xiaoping Liao, Mattheos Koffas, Yixin Chen, Hongwu Ma, and Yinjie J Tang. Large language model for knowledge synthesis and ai-enhanced biomanufacturing. Trends in Biotechnology, Mar 2025. find
447. Xiangci Li and Jessica Ouyang. Related work and citation text generation: A survey. In Yaser Al-Onaizan, Mohit Bansal, and Yun-Nung Chen, editors, Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, pages 13846–13864, Miami, Florida, USA, November 2024. Associatio… find
448. Xiangci Li and Jessica Ouyang. Explaining relationships among research papers. arXiv preprint arXiv:2402.13426, 2024.
449. Xiangci Li and Jessica Ouyang. Related work and citation text generation: A survey. arXiv preprint arXiv:2404.11588, 2024. find
450. Xiangci Li, Yi-Hui Lee, and Jessica Ouyang. Cited text spans for citation text generation. arXiv preprint arXiv:2309.06365, 2023. — [arXiv:2309.06365](https://arxiv.org/abs/2309.06365) find
451. Xiangyu Li and Jingqiang Chen. Scirgc: Multi-granularity citation recommendation and citation sentence preference alignment. arXiv preprint arXiv:2505.20103, 2025. — [arXiv:2505.20103](https://arxiv.org/abs/2505.20103) find
452. Xiaobo Li, Yu Che, Linjiang Chen, Tao Liu, Kewei Wang, Lunjie Liu, Haofan Yang, Edward O Pyzer-Knapp, and Andrew I Cooper. Sequential closed-loop bayesian optimization as a guide for organic molecular metallophotocatalyst formulation discovery. Nature Chemistry, 16(8):1286–1294, Jun 2024. find
453. Yifei Li, Hanane Nour Moussa, Ziru Chen, Shijie Chen, Botao Yu, Mingyi Xue, Benjamin Burns, Tzu-Yao Chiu, Vishal Dey, Zitong Lu, et al. Autosdt: Scaling data-driven discovery tasks toward open co-scientists. arXiv preprint arXiv:2506.08140, 2025. find
454. Yugang Li, Baizhou Wu, Yuqi Huang, and Shenghua Luan. Developing trustworthy artificial intelligence: insights from research on interpersonal, human-automation, and human-ai trust. Frontiers in Psychology, 15:1382693, Apr 2024. find
455. Zekun Li, Xianjun Yang, Kyuri Choi, Wanrong Zhu, Ryan Hsieh, HyeonJung Kim, Jin Hyuk Lim, Sungyoung Ji, Byungju Lee, Xifeng Yan, et al. Mmsci: A dataset for graduate-level multi-discipline multimodal scientific understanding. arXiv preprint arXiv:2407.04903, 2024.
456. Zhaoyu Li, Jialiang Sun, Logan Murphy, Qidong Su, Zenan Li, Xian Zhang, Kaiyu Yang, and Xujie Si. A survey on deep learning for theorem proving. arXiv preprint arXiv:2404.09939, 2024. find
457. Zhi Li and Xiaozhu Zou. A review on personalized academic paper recommendation. Comput. Inf. Sci., 12(1):33–43, Jan 2019. find
458. Zhuofan Li and Corey M Abramson. Ethnography and machine learning: Synergies and new directions. arXiv preprint arXiv:2412.06087, 2024. — [arXiv:2412.06087](https://arxiv.org/abs/2412.06087) find
459. Ziming Li, Qianbo Zang, David Ma, Jiawei Guo, Tuney Zheng, Minghao Liu, Xinyao Niu, Yue Wang, Jian Yang, Jiaheng Liu, et al. Autokaggle: A multi-agent framework for autonomous data science competitions. arXiv preprint arXiv:2410.20424, 2024. find
460. Haotong Liang, Chuangye Wang, Heshan Yu, Dylan Kirsch, Rohit Pant, Austin McDannald, A Gilad Kusne, Ji-Cheng Zhao, and Ichiro Takeuchi. Real-time experiment-theory closed-loop interaction for autonomous materials science. arXiv preprint arXiv:2410.17430, 2024. — [arXiv:2410.17430](https://arxiv.org/abs/2410.17430) find
461. Jing Liang. The application of artificial intelligence-assisted technology in cultural and creative product design. Scientific Reports, 14(1):31069, Dec 2024. find
462. Siting Liang and Daniel Sonntag. Explainable biomedical claim verification with large language models. arXiv preprint arXiv:2502.21014, 2025. — [arXiv:2502.21014](https://arxiv.org/abs/2502.21014) find
463. Weixin Liang, Yuhui Zhang, Hancheng Cao, Binglu Wang, Daisy Yi Ding, Xinyu Yang, Kailas Vodrahalli, Siyu He, Daniel Scott Smith, Yian Yin, et al. Can large language models provide useful feedback on research papers? a large-scale empirical analysis. NEJM AI, 1(8):AIoa2400196, Jul 2024. find
464. Xun Liang, Jiawei Yang, Yezhaohui Wang, Chen Tang, Zifan Zheng, Shichao Song, Zehao Lin, Yebin Yang, Simin Niu, Hanyu Wang, et al. Surveyx: Academic survey automation via large language models. arXiv preprint arXiv:2502.14776, 2025. — [arXiv:2502.14776](https://arxiv.org/abs/2502.14776) find
465. Zhenwen Liang, Kehan Guo, Gang Liu, Taicheng Guo, Yujun Zhou, Tianyu Yang, Jiajun Jiao, Renjie Pi, Jipeng Zhang, and Xiangliang Zhang. SceMQA: A scientific college entrance level multimodal question answering benchmark. In Lun-Wei Ku, Andre Martins, and Vivek Srikumar, editors, Proceedings of the 62… find
466. Zhehui Liao, Maria Antoniak, Inyoung Cheong, Evie Yu-Yen Cheng, Ai-Heng Lee, Kyle Lo, Joseph Chee Chang, and Amy X Zhang. Llms as research tools: A large scale survey of researchers’ usage and perceptions. arXiv preprint arXiv:2411.05025, 2024. — [arXiv:2411.05025](https://arxiv.org/abs/2411.05025) find
467. Daniel J. Liebling, Malcolm Kane, Madeleine Grunde-McLaughlin, Ian Lang, Subhashini Venugopalan, and Michael Brenner. Towards AI-assisted academic writing. In Peter Jansen, Bhavana Dalvi Mishra, Harsh Trivedi, Bodhisattwa Prasad Majumder, Tom Hope, Tushar Khot, Doug Downey, and Eric Horvitz, editors… find
468. Cong William Lin and Wu Zhu. Divergent llm adoption and heterogeneous convergence paths in research writing. arXiv preprint arXiv:2504.13629, 2025. — [arXiv:2504.13629](https://arxiv.org/abs/2504.13629) find
469. Ethan Lin, Zhiyuan Peng, and Yi Fang. Evaluating and enhancing large language models for novelty assessment in scholarly publications. In Peter Jansen, Bhavana Dalvi Mishra, Harsh Trivedi, Bodhisattwa Prasad Majumder, Tom Hope, Tushar Khot, Doug Downey, and Eric Horvitz, editors, Proceedings of the… find
470. Haohan Lin, Zhiqing Sun, Sean Welleck, and Yiming Yang. Lean-star: Learning to interleave thinking and proving. arXiv preprint arXiv:2407.10040, 2024. find
471. Jialiang Lin, Jiaxin Song, Zhangping Zhou, Yidong Chen, and Xiaodong Shi. Automated scholarly paper review: Concepts, technologies, and challenges. Information fusion, 98:101830, Oct 2023. find
472. Jialiang Lin, Jiaxin Song, Zhangping Zhou, Yidong Chen, and Xiaodong Shi. Moprd: A multidisciplinary open peer review dataset. Neural Computing and Applications, 35(34):24191–24206, Sep 2023. find
473. Tung-Wei Lin, Runing Yang, Zain ul Abdeen, Alberto Sangiovanni-Vincentelli, Haibo Huang, and Ming Jin. Llms tackle meta-analysis: Automating scientific hypothesis generation with statistical rigor. In 2nd AI4Research Workshop: Towards a Knowledge-grounded Scientific Research Lifecycle, Dec 2024. find
474. Xinna Lin, Siqi Ma, Junjie Shan, Xiaojing Zhang, Shell Xu Hu, Tiannan Guo, Stan Z Li, and Kaicheng Yu. Biokgbench: A knowledge graph checking benchmark of ai agent for biomedical science. arXiv preprint arXiv:2407.00466, 2024.
475. Xuan Lin, Qingrui Liu, Hongxin Xiang, Daojian Zeng, and Xiangxiang Zeng. Enhancing chemical reaction and retrosynthesis prediction with large language model and dual-task learning. arXiv preprint arXiv:2505.02639, 2025. — [arXiv:2505.02639](https://arxiv.org/abs/2505.02639) find
476. Xule Lin. Cognitio emergens: Agency, dimensions, and dynamics in human-ai knowledge co-creation. arXiv preprint arXiv:2505.03105, 2025. — [arXiv:2505.03105](https://arxiv.org/abs/2505.03105) find
477. Zhicheng Lin. Beyond principlism: practical strategies for ethical ai use in research practices. AI and Ethics, pages 1–13, Oct 2024. find
478. Zhicheng Lin. Techniques for supercharging academic writing with generative ai. Nature Biomedical Engineering, pages 1–6, Mar 2024. find
479. Aixin Liu, Bei Feng, Bing Xue, Bingxuan Wang, Bochao Wu, Chengda Lu, Chenggang Zhao, Chengqi Deng, Chenyu Zhang, Chong Ruan, et al. Deepseek-v3 technical report. arXiv preprint arXiv:2412.19437, 2024. find
480. Bang Liu, Xinfeng Li, Jiayi Zhang, Jinlin Wang, Tanjin He, Sirui Hong, Hongzhang Liu, Shaokun Zhang, Kaitao Song, Kunlun Zhu, et al. Advances and challenges in foundation agents: From brain-inspired intelligence to evolutionary, collaborative, and safe systems. arXiv preprint arXiv:2504.01990, 2025. — [arXiv:2504.01990](https://arxiv.org/abs/2504.01990) find
481. Chengwei Liu, Chong Wang, Jiayue Cao, Jingquan Ge, Kun Wang, Lvye Zhang, Ming-Ming Cheng, Penghai Zhao, Tianlin Li, Xiaojun Jia, et al. A vision for auto research with llm agents. arXiv preprint arXiv:2504.18765, 2025. — [arXiv:2504.18765](https://arxiv.org/abs/2504.18765) find
482. Chengwu Liu, Jianhao Shen, Huajian Xin, Zhengying Liu, Ye Yuan, Haiming Wang, Wei Ju, Chuanyang Zheng, Yichun Yin, Lin Li, et al. Fimo: A challenge formal dataset for automated theorem proving. arXiv preprint arXiv:2309.04295, 2023. find
483. Chunwei Liu, Enrique Noriega-Atala, Adarsh Pyarelal, Clayton T Morrison, and Mike Cafarella. Variable extraction for model recovery in scientific literature. In Peter Jansen, Bhavana Dalvi Mishra, Harsh Trivedi, Bodhisattwa Prasad Majumder, Tom Hope, Tushar Khot, Doug Downey, and Eric Horvitz, edito… find
484. Fengming Liu and Shubin Yu. Step further towards automated social science: An ai-powered interview platform. Available at SSRN, Apr 2024. find
485. Haokun Liu, Yangqiaoyu Zhou, Mingxuan Li, Chenfei Yuan, and Chenhao Tan. Literature meets data: A synergistic approach to hypothesis generation. arXiv preprint arXiv:2410.17309, 2024.
486. Haokun Liu, Sicong Huang, Jingyu Hu, Yangqiaoyu Zhou, and Chenhao Tan. Hypobench: Towards systematic and principled benchmarking for hypothesis generation. arXiv preprint arXiv:2504.11524, 2025. — [arXiv:2504.11524](https://arxiv.org/abs/2504.11524) find
487. Haoyu Liu, Yifu Tang, Zizhao Zhang, Zeyu Zheng, and Tingyu Zhu. Large language model assisted experiment design with generative human-behavior agents. In 2024 Winter Simulation Conference (WSC), pages 2751–2762. IEEE, Dec 2024. find
488. Jiachang Liu, Qi Zhang, Chongyang Shi, Usman Naseem, Shoujin Wang, and Ivor Tsang. Causal intervention for abstractive related work generation. arXiv preprint arXiv:2305.13685, 2023. find
489. Jiaheng Liu, Dawei Zhu, Zhiqi Bai, Yancheng He, Huanxuan Liao, Haoran Que, Zekun Wang, Chenchen Zhang, Ge Zhang, Jiebin Zhang, et al. A comprehensive survey on long context language modeling. arXiv preprint arXiv:2503.17407, 2025.
490. Mengchen Liu, Qixiu Li, Dongdong Chen, Dong Chen, Jianmin Bao, and Yunsheng Li. Synchart: Synthesizing charts from language models. arXiv preprint arXiv:2409.16517, 2024. — [arXiv:2409.16517](https://arxiv.org/abs/2409.16517) find
491. Ruibo Liu, Ruixin Yang, Chenyan Jia, Ge Zhang, Denny Zhou, Andrew M Dai, Diyi Yang, and Soroush Vosoughi. Training socially aligned language models in simulated human society. arXiv preprint arXiv:2305.16960, 2, 2023. find
492. Ryan Liu and Nihar B Shah. Reviewergpt? an exploratory study on using large language models for paper reviewing. arXiv preprint arXiv:2306.00622, 2023. find
493. Shuaiqi Liu, Jiannong Cao, Ruosong Yang, and Zhiyuan Wen. Generating a structured summary of numerous academic papers: Dataset and method. arXiv preprint arXiv:2302.04580, 2023. — [arXiv:2302.04580](https://arxiv.org/abs/2302.04580) find
494. Siyi Liu, Chen Gao, and Yong Li. Large language model agent for hyper-parameter optimization. arXiv preprint arXiv:2402.01881, 2024. find
495. Sizhe Liu, Yizhou Lu, Siyu Chen, Xiyang Hu, Jieyu Zhao, Yingzhou Lu, and Yue Zhao. Drugagent: Automating ai-aided drug discovery programming through llm multi-agent collaboration. arXiv preprint arXiv:2411.15692, 2024. find
496. Wanhao Liu, Zonglin Yang, Jue Wang, Lidong Bing, Di Zhang, Dongzhan Zhou, Yuqiang Li, Houqiang Li, Erik Cambria, and Wanli Ouyang. Moose-chem3: Toward experiment-guided hypothesis ranking via simulated experimental feedback. arXiv preprint arXiv:2505.17873, 2025. find
497. Xiao Liu, Xinyi Dong, Xinyang Gao, Yansong Feng, and Xun Pang. Improving research idea generation through data: An empirical investigation in social science. arXiv preprint arXiv:2505.21396, 2025. — [arXiv:2505.21396](https://arxiv.org/abs/2505.21396) find
498. Xiaochuan Liu, Ruihua Song, Xiting Wang, and Xu Chen. Select, read, and write: A multi-agent framework of full-text-based related work generation. arXiv preprint arXiv:2505.19647, 2025. find
499. Yan Liu, Zonglin Yang, Soujanya Poria, Thanh-Son Nguyen, and Erik Cambria. Harnessing large language models for scientific novelty detection. arXiv preprint arXiv:2505.24615, 2025. — [arXiv:2505.24615](https://arxiv.org/abs/2505.24615) find
500. Yijun Liu, Jinzheng Yu, Yang Xu, Zhongyang Li, and Qingfu Zhu. A survey on transformer context extension: Approaches and evaluation. arXiv preprint arXiv:2503.13299, 2025. — [arXiv:2503.13299](https://arxiv.org/abs/2503.13299) find
501. Yiren Liu, Si Chen, Haocong Cheng, Mengxia Yu, Xiao Ran, Andrew Mo, Yiliu Tang, and Yun Huang. How ai processing delays foster creativity: Exploring research question co-creation with an llm-based agent. In Proceedings of the 2024 CHI Conference on Human Factors in Computing Systems, pages 1–25, May… find
502. Yujie Liu, Zonglin Yang, Tong Xie, Jinjie Ni, Ben Gao, Yuqiang Li, Shixiang Tang, Wanli Ouyang, Erik Cambria, and Dongzhan Zhou. Researchbench: Benchmarking llms in scientific discovery via inspiration-based task decomposition. arXiv preprint arXiv:2503.21248, 2025. find
503. Yuyang Liu, Liuzhenghao Lv, Xiancheng Zhang, Li Yuan, and Yonghong Tian. Bioprobench: Comprehensive dataset and benchmark in biological protocol understanding and reasoning. arXiv preprint arXiv:2505.07889, 2025. — [arXiv:2505.07889](https://arxiv.org/abs/2505.07889) find
504. Zijun Liu, Kaiming Liu, Yiqi Zhu, Xuanyu Lei, Zonghan Yang, Zhenhe Zhang, Peng Li, and Yang Liu. Aigs: Generating science from ai-powered automated falsification. arXiv preprint arXiv:2411.11910, 2024. — [arXiv:2411.11910](https://arxiv.org/abs/2411.11910) find
505. Stanley Lo, Sterling G Baird, Joshua Schrier, Ben Blaiszik, Nessa Carson, Ian Foster, Andrés Aguilar-Granda, Sergei V Kalinin, Benji Maruyama, Maria Politi, et al. Review of low-cost self-driving laboratories in chemistry and materials science: the “frugal twin” concept. Digital Discovery, 3(5): 842… find
506. Joseph R Loffredo and Suyeol Yun. Agent-enhanced large language models for researching political institutions. arXiv preprint arXiv:2503.13524, 2025. — [arXiv:2503.13524](https://arxiv.org/abs/2503.13524) find
507. Renze Lou, Hanzi Xu, Sijia Wang, Jiangshu Du, Ryo Kamoi, Xiaoxin Lu, Jian Xie, Yuxuan Sun, Yusen Zhang, Jihyun Janice Ahn, et al. Aaar-1.0: Assessing ai’s potential to assist research. arXiv preprint arXiv:2410.22394, 2024. — [arXiv:2410.22394](https://arxiv.org/abs/2410.22394) find
508. Anton Lozhkov, Raymond Li, Loubna Ben Allal, Federico Cassano, Joel Lamy-Poirier, Nouamane Tazi, Ao Tang, Dmytro Pykhtar, Jiawei Liu, Yuxiang Wei, et al. Starcoder 2 and the stack v2: The next generation. arXiv preprint arXiv:2402.19173, 2024. find
509. Chris Lu, Cong Lu, Robert Tjarko Lange, Jakob Foerster, Jeff Clune, and David Ha. The ai scientist: Towards fully automated open-ended scientific discovery. arXiv preprint arXiv:2408.06292, 2024.
510. Cong Lu, Shengran Hu, and Jeff Clune. Beyond benchmarking: Automated capability discovery via model self-exploration. In Language Gamification-NeurIPS 2024 Workshop, Oct 2024. find
511. Yingzhou Lu, Yaojun Hu, and Chenhao Li. Drugclip: Contrastive drug-disease interaction for drug repurposing. arXiv preprint arXiv:2407.02265, 2024. — [arXiv:2407.02265](https://arxiv.org/abs/2407.02265) find
512. Hewitt Luke, Ashokkumar Ashwini, Ghezae Isaias, and Willer Robb. Predicting results of social science experiments using large language models, Aug 2024. URL https://samim.io/dl/Predicting%20results%20of%20social%20science% 20experiments%20using%20large%20language%20models.pdf. Predicting Results of… ↗
513. Erpai Luo, Jinmeng Jia, Yifan Xiong, Xiangyu Li, Xiaobo Guo, Baoqi Yu, Lei Wei, and Xuegong Zhang. Benchmarking ai scientists in omics data-driven biological research. arXiv preprint arXiv:2505.08341, 2025. — [arXiv:2505.08341](https://arxiv.org/abs/2505.08341) find
514. Junyu Luo, Cheng Qian, Lucas Glass, and Fenglong Ma. Clinical trial retrieval via multi-grained similarity learning. In Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 2950–2954, Jul 2024. find
515. Man Luo, Zikai Xie, Huirong Li, Baicheng Zhang, Jiaqi Cao, Yan Huang, Hang Qu, Qing Zhu, Linjiang Chen, Jun Jiang, et al. Physics-informed, dual-objective optimization of high-entropy-alloy nanozymes by a robotic ai chemist. Matter, 8(4), Apr 2025. find
516. Shunyang Luo, Yuqi Tang, Mingyuan Jiang, Kehua Feng, Qiang Zhang, and Keyan Ding. Generating multiple choice questions from scientific literature via large language models. In 2024 IEEE International Conference on Knowledge Graph (ICKG), pages 219–226, Feb 2024. doi: 10.1109/ICKG63256. 2024.00035. — [doi:10.1109/ickg63256](https://doi.org/10.1109/ickg63256) find
517. Xiaoliang Luo, Akilles Rechardt, Guangzhi Sun, Kevin K Nejad, Felipe Yáñez, Bati Yilmaz, Kangjoo Lee, Alexandra O Cohen, Valentina Borghesani, Anton Pashkov, et al. Large language models surpass human experts in predicting neuroscience results. Nature human behaviour, 9(2):305–315, Nov 2025. find
518. Zheheng Luo, Qianqian Xie, and Sophia Ananiadou. Citationsum: Citation-aware graph contrastive learning for scientific paper summarization. In Proceedings of the ACM web conference 2023, pages 1843–1852, Apr 2023. find
519. Ziming Luo, Zonglin Yang, Zexin Xu, Wei Yang, and Xinya Du. Llm4sr: A survey on large language models for scientific research. arXiv preprint arXiv:2501.04306, 2025. find
520. Andres M. Bran, Sam Cox, Oliver Schilter, Carlo Baldassari, Andrew D White, and Philippe Schwaller. Augmenting large language models with chemistry tools. Nature Machine Intelligence, 6(5):525–535, May 2024. find
521. Pingchuan Ma, Tsun-Hsuan Wang, Minghao Guo, Zhiqing Sun, Joshua B Tenenbaum, Daniela Rus, Chuang Gan, and Wojciech Matusik. Llm and simulation as bilevel optimizers: A new paradigm to advance physical scientific discovery. arXiv preprint arXiv:2405.09783, 2024. find
522. Qinyu Ma, Yuhao Zhou, and Jianfeng Li. Automated retrosynthesis planning of macromolecules using large language models and knowledge graphs. Macromolecular Rapid Communications, page 2500065, Feb 2025. find
523. Shutian Ma, Heng Zhang, Chengzhi Zhang, and Xiaozhong Liu. Chronological citation recommendation with time preference. Scientometrics, 126:2991–3010, Feb 2021. find
524. Yubo Ma, Zhibin Gou, Junheng Hao, Ruochen Xu, Shuohang Wang, Liangming Pan, Yujiu Yang, Yixin Cao, and Aixin Sun. SciAgent: Tool-augmented language models for scientific reasoning. In Yaser Al-Onaizan, Mohit Bansal, and Yun-Nung Chen, editors, Proceedings of the 2024 Conference on Empirical Methods…
525. Kojiro Machi, Seiji Akiyama, Yuuya Nagata, and Masaharu Yoshioka. A framework for reviewing the results of automated conversion of structured organic synthesis procedures from the literature. Digital Discovery, 4(1):172–180, Nov 2025. find
526. Benjamin P MacLeod, Fraser GL Parlane, Thomas D Morrissey, Florian Häse, Loïc M Roch, Kevan E Dettelbach, Raphaell Moreira, Lars PE Yunker, Michael B Rooney, Joseph R Deeth, et al. Self-driving laboratory for accelerated discovery of thin-film materials. Science Advances, 6(20):eaaz8867, 2020. find
527. Puja Maharjan. Benchmark for evaluation and analysis of citation recommendation models. arXiv preprint arXiv:2412.07713, 2024. — [arXiv:2412.07713](https://arxiv.org/abs/2412.07713) find
528. Bodhisattwa Prasad Majumder, Harshit Surana, Dhruv Agarwal, Sanchaita Hazra, Ashish Sabharwal, and Peter Clark. Position: data-driven discovery with large generative models. In Forty-first International Conference on Machine Learning, May 2024.
529. Bodhisattwa Prasad Majumder, Harshit Surana, Dhruv Agarwal, Bhavana Dalvi Mishra, Abhijeetsingh Meena, Aryan Prakhar, Tirth Vora, Tushar Khot, Ashish Sabharwal, and Peter Clark. Discoverybench: Towards data-driven discovery with large language models. arXiv preprint arXiv:2407.01725, 2024. find
530. Sepideh Maleki, Jan-Christian Huetter, Kangway V Chuang, David Richmond, Gabriele Scalia, and Tommaso Biancalani. Efficient fine-tuning of single-cell foundation models enables zero-shot molecular perturbation prediction. arXiv preprint arXiv:2412.13478, 2024. — [arXiv:2412.13478](https://arxiv.org/abs/2412.13478) find
531. Indrajeet Mandal, Jitendra Soni, Mohd Zaki, Morten M Smedskjaer, Katrin Wondraczek, Lothar Wondraczek, Nitya Nand Gosvami, and NM Krishnan. Autonomous microscopy experiments through large language model agents. arXiv preprint arXiv:2501.10385, 2024. — [arXiv:2501.10385](https://arxiv.org/abs/2501.10385) find
532. Benjamin S Manning, Kehang Zhu, and John J Horton. Automated social science: Language models as scientist and subjects. Technical report, National Bureau of Economic Research, Apr 2024. find
533. Nacef Ben Mansour, Hamed Rahimi, and Motasem Alrahabi. How well do large language models extract keywords? a systematic evaluation on scientific corpora. In Peter Jansen, Bhavana Dalvi Mishra, Harsh Trivedi, Bodhisattwa Prasad Majumder, Tom Hope, Tushar Khot, Doug Downey, and Eric Horvitz, editors,… find
534. David M Markowitz. From complexity to clarity: How ai enhances perceptions of scientists and the public’s understanding of science. PNAS nexus, 3(9):pgae387, Sep 2024. find
535. Anna Martin-Boyle, Aahan Tyagi, Marti A Hearst, and Dongyeop Kang. Shallow synthesis of knowledge in gpt-generated texts: A case study in automatic related work composition. arXiv preprint arXiv:2402.12255, 2024.
536. M Maruf, Arka Daw, Kazi Sajeed Mehrab, Harish Babu Manogaran, Abhilash Neog, Medha Sawhney, Mridul Khurana, James Balhoff, Yasin Bakis, Bahadir Altintas, et al. Vlm4bio: A benchmark dataset to evaluate pretrained vision-language models for trait discovery from biological images. Advances in Neural I… find
537. Ahmed Masry, Do Xuan Long, Jia Qing Tan, Shafiq Joty, and Enamul Hoque. ChartQA: A benchmark for question answering about charts with visual and logical reasoning. In Smaranda Muresan, Preslav Nakov, and Aline Villavicencio, editors, Findings of the Association for Computational Linguistics: ACL 202…
538. Ahmed Masry, Mehrad Shahmohammadi, Md Rizwan Parvez, Enamul Hoque, and Shafiq Joty. ChartInstruct: Instruction tuning for chart comprehension and reasoning. In Lun-Wei Ku, Andre Martins, and Vivek Srikumar, editors, Findings of the Association for Computational Linguistics: ACL 2024, pages 10387–104… find
539. Ahmed Masry, Megh Thakkar, Aayush Bajaj, Aaryaman Kartha, Enamul Hoque, and Shafiq Joty. ChartGemma: Visual instruction-tuning for chart reasoning in the wild. In Owen Rambow, Leo Wanner, Marianna Apidianaki, Hend Al-Khalifa, Barbara Di Eugenio, Steven Schockaert, Kareem Darwish, and Apoorv Agarwal,… find
540. Shray Mathur, Noah van der Vleuten, Kevin G Yager, and Esther Tsai. Vision: A modular ai assistant for natural human-instrument interaction at scientific user facilities. Machine Learning: Science and Technology, Jun 2025. find
541. Blakeley B McShane, David Gal, and Adam Duhachek. Artificial intelligence and dichotomania. Judgment and Decision Making, 20:e23, Apr 2025. find
542. Lennart Meincke, Karan Girotra, Gideon Nave, Christian Terwiesch, and Karl T. Ulrich. Using large language models for idea generation in innovation, Aug 2024. SSRN. find
543. Lennart Meincke, Ethan R. Mollick, and Christian Terwiesch. Prompting diverse ideas: Increasing ai idea variance, Feb 2024. SSRN. find
544. Chuizheng Meng, Sam Griesemer, Defu Cao, Sungyong Seo, and Yan Liu. When physics meets machine learning: A survey of physics-informed machine learning. Machine Learning for Computational Science and Engineering, 1(1):1–23, May 2025. find
545. Fanqing Meng, Wenqi Shao, Quanfeng Lu, Peng Gao, Kaipeng Zhang, Yu Qiao, and Ping Luo. ChartAssistant: A universal chart multimodal language model via chart-to-table pre-training and multitask instruction tuning. In Lun-Wei Ku, Andre Martins, and Vivek Srikumar, editors, Findings of the Association… find
546. Fanqing Meng, Wenqi Shao, Quanfeng Lu, Peng Gao, Kaipeng Zhang, Yu Qiao, and Ping Luo. Chartas-sisstant: A universal chart multimodal language model via chart-to-table pre-training and multitask instruction tuning. arXiv preprint arXiv:2401.02384, 2024. — [arXiv:2401.02384](https://arxiv.org/abs/2401.02384) find
547. George Benneh Mensah. Artificial intelligence and ethics: a comprehensive review of bias mitigation, transparency, and accountability in ai systems. Preprint, November, 10(1), Nov 2023. find
548. Amil Merchant, Simon Batzner, Samuel S Schoenholz, Muratahan Aykol, Gowoon Cheon, and Ekin Dogus Cubuk. Scaling deep learning for materials discovery. Nature, 624(7990):80–85, Nov 2023. find
549. Dasha Metropolitansky and Jonathan Larson. Towards effective extraction and evaluation of factual claims. arXiv preprint arXiv:2502.10855, 2025.
550. Ning Miao, Yee Whye Teh, and Tom Rainforth. Selfcheck: Using llms to zero-shot check their own step-by-step reasoning. arXiv preprint arXiv:2308.00436, 2023. find
551. Pawel Mieszczanek, Peter Corke, Courosh Mehanian, Paul D Dalton, and Dietmar W Hutmacher. Towards industry-ready additive manufacturing: Ai-enabled closed-loop control for 3d melt elec-trowriting. Communications Engineering, 3(1):158, 2024. find
552. Xinyi Mou, Xuanwen Ding, Qi He, Liang Wang, Jingcong Liang, Xinnong Zhang, Libo Sun, Jiayu Lin, Jie Zhou, Xuanjing Huang, et al. From individual to society: A survey on social simulation driven by large language model-based agents. arXiv preprint arXiv:2412.03563, 2024. — [arXiv:2412.03563](https://arxiv.org/abs/2412.03563) find
553. Omar Moured, Sara Alzalabny, Anas Osman, Thorsten Schwarz, Karin Müller, and Rainer Stiefelhagen. Chartformer: A large vision language model for converting chart images into tactile accessible svgs. In International Conference on Computers Helping People with Special Needs, pages 299–305. Springer,… find
554. Austin M Mroz, Annabel R Basford, Friedrich Hastedt, Isuru Shavindra Jayasekera, Irea Mosquera-Lois, Ruby Sedgwick, Pedro J Ballester, Joshua D Bocarsly, Ehecatl Antonio del Río Chanona, Matthew L Evans, et al. Cross-disciplinary perspectives on the potential for artificial intelligence across chemi… find
555. Panitan Muangkammuen, Fumiyo Fukumoto, Jiyi Li, and Yoshimi Suzuki. Exploiting labeled and unlabeled data via transformer fine-tuning for peer-review score prediction. In Findings of the Association for Computational Linguistics: EMNLP 2022, pages 2233–2240, Dec 2022. find
556. Arief Purnama Muharram and Ayu Purwarianti. Enhancing natural language inference performance with knowledge graph for covid-19 automated fact-checking in indonesian language. arXiv preprint arXiv:2409.00061, 2024. — [arXiv:2409.00061](https://arxiv.org/abs/2409.00061) find
557. Praveen Kumar Myakala, Anil Kumar Jonnalagadda, and Chiranjeevi Bura. Federated learning and data privacy: A review of challenges and opportunities. International Journal of Research Publication and Reviews, 5(12):10–55248, Jan 2024. find
558. Sheshera Mysore, Debarati Das, Hancheng Cao, and Bahareh Sarrafzadeh. Prototypical human-ai collaboration behaviors from llm-assisted writing in the wild. arXiv preprint arXiv:2505.16023, 2025. find
559. Inderjeet Nair, Jiaye Tan, Xiaotian Su, Anne Gere, Xu Wang, and Lu Wang. Closing the loop: Learning to generate writing feedback via language model simulated student revisions. arXiv preprint arXiv:2410.08058, 2024. find
560. Siddharth Narayanan, James D Braza, Ryan-Rhys Griffiths, Manu Ponnapati, Albert Bou, Jon Laurent, Ori Kabeli, Geemi Wellawatte, Sam Cox, Samuel G Rodriques, et al. Aviary: training language agents on challenging scientific tasks. arXiv preprint arXiv:2412.21154, 2024. find
561. Deepak Nathani, Lovish Madaan, Nicholas Roberts, Nikolay Bashlykov, Ajay Menon, Vincent Moens, Amar Budhiraja, Despoina Magka, Vladislav Vorotilov, Gaurav Chaurasia, et al. Mlgym: A new framework and benchmark for advancing ai research agents. arXiv preprint arXiv:2502.14499, 2025. find
562. Springer Nature. Snapp: Springer nature’s https://www.springernature.com/gp/snapp, Dec 2023. next-generation peer review system. ↗
563. Vladimir Naumov, Diana Zagirova, Sha Lin, Yupeng Xie, Wenhao Gou, Anatoly Urban, Nina Tikhonova, Khadija Alawi, Mike Durymanov, Fedor Galkin, et al. Dora ai scientist: Multi-agent virtual research team for scientific exploration discovery and automated report generation. bioRxiv, Mar 2025. find
564. Benjamin Newman, Yoonjoo Lee, Aakanksha Naik, Pao Siangliulue, Raymond Fok, Juho Kim, Daniel S Weld, Joseph Chee Chang, and Kyle Lo. ArxivDIGESTables: Synthesizing scientific literature into tables using language models. In Yaser Al-Onaizan, Mohit Bansal, and Yun-Nung Chen, editors, Proceedings of t… find
565. Izzy Newsham, Luka Kovačević, Richard Moulange, Nan Rosemary Ke, and Sach Mukherjee. Large language models for zero-shot inference of causal structures in biology. arXiv preprint arXiv:2503.04347, 2025. — [arXiv:2503.04347](https://arxiv.org/abs/2503.04347) find
566. Andy Nguyen, Yvonne Hong, Belle Dang, and Xiaoshan Huang. Human-ai collaboration patterns in ai-assisted academic writing. Studies in Higher Education, 49(5):847–864, Oct 2024. find
567. Bo Ni and Markus J Buehler. Mechagents: Large language model multi-agent collaborations can solve mechanics problems, generate new data, and integrate knowledge. Extreme Mechanics Letters, 67: 102131, Mar 2024. find
568. Ziqi Ni, Yahao Li, Kaijia Hu, Kunyuan Han, Ming Xu, Xingyu Chen, Fengqi Liu, Yicong Ye, and Shuxin Bai. Matpilot: an llm-enabled ai materials scientist under the framework of human-machine collaboration. arXiv preprint arXiv:2411.08063, 2024. — [arXiv:2411.08063](https://arxiv.org/abs/2411.08063) find
569. Harshit Nigam, Manasi Patwardhan, Lovekesh Vig, and Gautam Shroff. An interactive co-pilot for accelerated research ideation. In Su Lin Blodgett, Amanda Cercas Curry, Sunipa Dev, Michael Madaio, Ani Nenkova, Diyi Yang, and Ziang Xiao, editors, Proceedings of the Third Workshop on Bridging Human–Comp… find
570. Harshit Nigam, Manasi Patwardhan, Lovekesh Vig, and Gautam Shroff. Acceleron: A tool to accelerate research ideation. arXiv preprint arXiv:2403.04382, 2024. — [arXiv:2403.04382](https://arxiv.org/abs/2403.04382) find
571. Erik Nijkamp, Bo Pang, Hiroaki Hayashi, Lifu Tu, Huan Wang, Yingbo Zhou, Silvio Savarese, and Caiming Xiong. Codegen: An open large language model for code with multi-turn program synthesis. arXiv preprint arXiv:2203.13474, 2022. find
572. Kun-Peng Ning, Shuo Yang, Yuyang Liu, Jia-Yu Yao, Zhenhui Liu, Yonghong Tian, Yibing Song, and Li Yuan. PiCO: Peer review in LLMs based on consistency optimization. In The Thirteenth International Conference on Learning Representations, Jan 2025. URL https://openreview.net/forum?id= sfQ6XpApfS. ↗
573. Kazuya Nishimura, Kuniaki Saito, Tosho Hirasawa, and Yoshitaka Ushiku. Toward related work generation with structure and novelty statement. In Proceedings of the Fourth Workshop on Scholarly Document Processing (SDP 2024), pages 38–57, Aug 2024. find
574. Haoyi Niu, Jianming Hu, Guyue Zhou, and Xianyuan Zhan. A comprehensive survey of cross-domain policy transfer for embodied agents. arXiv preprint arXiv:2402.04580, 2024. — [arXiv:2402.04580](https://arxiv.org/abs/2402.04580) find
575. Liang Niu, Nian Xue, and Christina Pöpper. Unveiling the sentinels: Assessing ai performance in cybersecurity peer review. arXiv preprint arXiv:2309.05457, 2023. — [arXiv:2309.05457](https://arxiv.org/abs/2309.05457) find
576. Alexander Novikov, Ngân Vu, Marvin Eisenberger, Emilien Dupont, Po-Sen Huang, Adam Zsolt Wagner, Sergey Shirobokov, Borislav Kozlovskii, Francisco JR Ruiz, Abbas Mehrabian, et al. Alphaevolve: A coding agent for scientific and algorithmic discovery. Google DeepMind, Jun 2025.
577. Charles O’Neill, Tirthankar Ghosal, Roberta Răileanu, Mike Walmsley, Thang Bui, Kevin Schawinski, and Ioana Ciucă. Sparks of science: Hypothesis generation using structured paper data. arXiv preprint arXiv:2504.12976, 2025.
578. OpenAI. Introducing deep research, Feb 2025. introducing-deep-research/. URL https://openai.com/index/ ↗
579. OpenAI. Gpt-4o search preview, May 2025. URL https://platform.openai.com/docs/ models/gpt-4o-search-preview. ↗
580. Raúl Ortega and José Manuel Gómez-Pérez. Sciclaims: An end-to-end generative system for biomedical claim analysis. arXiv preprint arXiv:2503.18526, 2025.
581. Zhinya Kawa Othman, Mohamed Mustaf Ahmed, Olalekan John Okesanya, Adamu Muhammad Ibrahim, Shuaibu Saidu Musa, Bryar A Hassan, Lanja Ibrahim Saeed, and Don Eliseo Lucero-Prisno III. Advancing drug discovery and development through gpt models: a review on challenges, innovations and future prospects.… find
582. Yixin Ou, Yujie Luo, Jingsheng Zheng, Lanning Wei, Shuofei Qiao, Jintian Zhang, Da Zheng, Huajun Chen, and Ningyu Zhang. Automind: Adaptive knowledgeable agent for automated data science. arXiv preprint arXiv:2506.10974, 2025. — [arXiv:2506.10974](https://arxiv.org/abs/2506.10974) find
583. Colleen Ovelman, Shannon Kugley, Gerald Gartlehner, and Meera Viswanathan. The use of a large language model to create plain language summaries of evidence reviews in healthcare: A feasibility study. Cochrane Evidence Synthesis and Methods, 2(2):e12041, Feb 2024. find
584. Ipek Ozkaya. Application of large language models to software engineering tasks: Opportunities, risks, and implications. IEEE Software, 40(3):4–8, Apr 2023. find
585. Vishakh Padmakumar and He He. Machine-in-the-loop rewriting for creative image captioning. arXiv preprint arXiv:2111.04193, 2021. find
586. Vishakh Padmakumar and He He. Does writing with language models reduce content diversity? arXiv preprint arXiv:2309.05196, 2023. find
587. Ankit Pal, Logesh Kumar Umapathi, and Malaikannan Sankarasubbu. Medmcqa: A large-scale multi-subject multi-choice dataset for medical domain question answering. In Conference on health, inference, and learning, pages 248–260. PMLR, Apr 2022. — MedMCQA : A Large-scale Multi-Subject Multi-Choice Dataset for Medical domain Question Answering
588. Liangming Pan, Xiaobao Wu, Xinyuan Lu, Anh Tuan Luu, William Yang Wang, Min-Yen Kan, and Preslav Nakov. Fact-checking complex claims with program-guided reasoning. arXiv preprint arXiv:2305.12744, 2023.
589. Liangming Pan, Yunxiang Zhang, and Min-Yen Kan. Investigating zero-and few-shot generalization in fact verification. arXiv preprint arXiv:2309.09444, 2023. find
590. Wenbo Pan, Zhichao Liu, Qiguang Chen, Xiangyang Zhou, Haining Yu, and Xiaohua Jia. The hidden dimensions of llm alignment: A multi-dimensional safety analysis. arXiv preprint arXiv:2502.09674, 2025. — [arXiv:2502.09674](https://arxiv.org/abs/2502.09674) find
591. Jing-Cheng Pang, Heng-Bo Fan, Pengyuan Wang, Jia-Hao Xiao, Nan Tang, Si-Hang Yang, Chengxing Jia, Sheng-Jun Huang, and Yang Yu. Empowering language models with active inquiry for deeper understanding. arXiv preprint arXiv:2402.03719, 2024. — [arXiv:2402.03719](https://arxiv.org/abs/2402.03719) find
592. Wei Pang, Kevin Qinghong Lin, Xiangru Jian, Xi He, and Philip Torr. Paper2poster: Towards multimodal poster automation from scientific papers. arXiv preprint arXiv:2505.21497, 2025. — [arXiv:2505.21497](https://arxiv.org/abs/2505.21497) find
593. Jong Inn Park, Maanas Taneja, Qianwen Wang, and Dongyeop Kang. Stealing creator’s workflow: A creator-inspired agentic framework with iterative feedback loop for improved scientific short-form generation. arXiv preprint arXiv:2504.18805, 2025. — [arXiv:2504.18805](https://arxiv.org/abs/2504.18805) find
594. Qizhi Pei, Lijun Wu, Kaiyuan Gao, Jinhua Zhu, Yue Wang, Zun Wang, Tao Qin, and Rui Yan. Leveraging biomolecule and natural language through multi-modal learning: A survey. arXiv preprint arXiv:2403.01528, 2024. — [arXiv:2403.01528](https://arxiv.org/abs/2403.01528) find
595. Vishnu S Pendyala, Karnavee Kamdar, and Kapil Mulchandani. Automated research review support using machine learning, large language models, and natural language processing. Electronics, 14(2): 256, Jan 2025. find
596. Dengyun Peng, Yuhang Zhou, Qiguang Chen, Jinhao Liu, Jingjing Chen, and Libo Qin. Dlpo: Towards a robust, efficient, and generalizable prompt optimization framework from a deep-learning perspective. arXiv preprint arXiv:2503.13413, 2025. find
597. Gal Peretz, Mousa Arraf, and Kira Radinsky. What if: Generating code to answer simulation questions in chemistry texts. In Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 1335–1344, Jul 2023. find
598. Jérémy Perez, Corentin Léger, Marcela Ovando-Tellez, Chris Foulon, Joan Dussauld, Pierre-Yves Oudeyer, and Clément Moulin-Frier. Cultural evolution in populations of large language models. arXiv preprint arXiv:2403.08882, 2024. — [arXiv:2403.08882](https://arxiv.org/abs/2403.08882) find
599. Huy Nhat Phan, Tien N Nguyen, Phong X Nguyen, and Nghi DQ Bui. Hyperagent: Generalist software engineering agents to solve coding tasks at scale. arXiv preprint arXiv:2409.16299, 2024. — [arXiv:2409.16299](https://arxiv.org/abs/2409.16299) find
600. Iratxe Pinedo, Mikel Larrañaga, and Ana Arruarte. Arzigo: A recommendation system for scientific articles. Information Systems, 122:102367, May 2024. find
601. Barbara Plank and Reinard van Dalen. Citetracked: A longitudinal dataset of peer reviews and citations. In Proceedings of the 4th Joint Workshop on Bibliometric-enhanced Information Retrieval and Natural Language Processing for Digital Libraries (BIRNDL 2019) co-located with the 42nd International A… find
602. Stanislas Polu and Ilya Sutskever. Generative language modeling for automated theorem proving. arXiv preprint arXiv:2009.03393, 2020.
603. Dinesh K Pradhan, Joyita Chakraborty, Prasenjit Choudhary, and Subrata Nandi. An automated conflict of interest based greedy approach for conference paper assignment system. Journal of Informetrics, 14 (2):101022, May 2020. find
604. Carolina Pradier, Lucía Céspedes, and Vincent Larivière. A smack of all neighbouring languages: How multilingual is scholarly communication? arXiv preprint arXiv:2504.21100, 2025. — [arXiv:2504.21100](https://arxiv.org/abs/2504.21100) find
605. Shraman Pramanick, Rama Chellappa, and Subhashini Venugopalan. Spiqa: A dataset for multimodal question answering on scientific papers. In The Thirty-eight Conference on Neural Information Processing Systems Datasets and Benchmarks Track, Jul 2024. URL https://openreview.net/forum?id= h3lddsY5nf. ↗
606. Adithya Pratapa and Teruko Mitamura. Estimating optimal context length for hybrid retrieval-augmented multi-document summarization. arXiv preprint arXiv:2504.12972, 2025. — [arXiv:2504.12972](https://arxiv.org/abs/2504.12972) find
607. S.V. Praveen, Pranshav Gajjar, Rajeev Kumar Ray, and Ashutosh Dutt. Crafting clarity: Leveraging large language models to decode consumer reviews. Journal of Retailing and Consumer Services, 81: 103975, Nov 2024. ISSN 0969-6989. doi: https://doi.org/10.1016/j.jretconser.2024.103975. URL https://www.… — [doi:10.1016/j.jretconser.2024.103975](https://doi.org/10.1016/j.jretconser.2024.103975) ↗
608. Dongqi Pu and Vera Demberg. Rst-lora: A discourse-aware low-rank adaptation for long document abstractive summarization. In Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), pages 22… find
609. Kevin Pu, KJ Kevin Feng, Tovi Grossman, Tom Hope, Bhavana Dalvi Mishra, Matt Latzke, Jonathan Bragg, Joseph Chee Chang, and Pao Siangliulue. Ideasynth: Iterative research idea development through evolving and composing idea facets with literature-grounded feedback. In Proceedings of the 2025 CHI Con… find
610. Yingming Pu, Tao Lin, and Hongyu Chen. Piflow: Principle-aware scientific discovery with multi-agent collaboration. arXiv preprint arXiv:2505.15047, 2025. — [arXiv:2505.15047](https://arxiv.org/abs/2505.15047) find
611. Sukannya Purkayastha, Zhuang Li, Anne Lauscher, Lizhen Qu, and Iryna Gurevych. Lazyreview a dataset for uncovering lazy thinking in nlp peer reviews. arXiv preprint arXiv:2504.11042, 2025. find
612. I Made Putrama and Péter Martinek. Heterogeneous data integration: Challenges and opportunities. Data in Brief, page 110853, Oct 2024. find
613. Edward O Pyzer-Knapp, Jed W Pitera, Peter WJ Staar, Seiji Takeda, Teodoro Laino, Daniel P Sanders, James Sexton, John R Smith, and Alessandro Curioni. Accelerating materials discovery using artificial intelligence, high performance computing and robotics. npj Computational Materials, 8(1):84, Apr 20… find
614. Chen Qian, Yufan Dang, Jiahao Li, Wei Liu, Zihao Xie, Yifei Wang, Weize Chen, Cheng Yang, Xin Cong, Xiaoyin Che, et al. Experiential co-learning of software-developing agents. arXiv preprint arXiv:2312.17025, 2023. find
615. Chen Qian, Wei Liu, Hongzhang Liu, Nuo Chen, Yufan Dang, Jiahao Li, Cheng Yang, Weize Chen, Yusheng Su, Xin Cong, et al. Chatdev: Communicative agents for software development. arXiv preprint arXiv:2307.07924, 2023.
616. Libo Qin, Xiao Xu, Wanxiang Che, Yue Zhang, and Ting Liu. Dynamic fusion network for multi-domain end-to-end task-oriented dialog. pages 6344–6354, July 2020. doi: 10.18653/v1/2020.acl-main.565. URL https://aclanthology.org/2020.acl-main.565/. ↗
617. Libo Qin, Shijue Huang, Qiguang Chen, Chenran Cai, Yudi Zhang, Bin Liang, Wanxiang Che, and Ruifeng Xu. Mmsd2. 0: Towards a reliable multi-modal sarcasm detection system. arXiv preprint arXiv:2307.07135, 2023.
618. Libo Qin, Qiguang Chen, Hao Fei, Zhi Chen, Min Li, and Wanxiang Che. What factors affect multimodal in-context learning? an in-depth exploration. arXiv preprint arXiv:2410.20482, 2024. — [arXiv:2410.20482](https://arxiv.org/abs/2410.20482) find
619. Libo Qin, Qiguang Chen, Xiachong Feng, Yang Wu, Yongheng Zhang, Yinghui Li, Min Li, Wanxiang Che, and Philip S Yu. Large language models meet nlp: A survey. arXiv preprint arXiv:2405.12819, 2024. — [arXiv:2405.12819](https://arxiv.org/abs/2405.12819) find
620. Libo Qin, Qiguang Chen, Yuhang Zhou, Zhi Chen, Yinghui Li, Lizi Liao, Min Li, Wanxiang Che, and Philip S Yu. A survey of multilingual large language models. Patterns, 6(1), Jan 2025. URL https://www.cell.com/patterns/fulltext/S2666-3899(24)00290-3. ↗
621. Yujia Qin, Shihao Liang, Yining Ye, Kunlun Zhu, Lan Yan, Yaxi Lu, Yankai Lin, Xin Cong, Xiangru Tang, Bill Qian, et al. Toolllm: Facilitating large language models to master 16000+ real-world apis. arXiv preprint arXiv:2307.16789, 2023.
622. Huachuan Qiu and Zhenzhong Lan. Interactive agents: Simulating counselor-client psychological counseling via role-playing llm-to-llm interactions. arXiv preprint arXiv:2408.15787, 2024.
623. Yansheng Qiu, Haoquan Zhang, Zhaopan Xu, Ming Li, Diping Song, Zheng Wang, and Kaipeng Zhang. Ai idea bench 2025: Ai research idea generation benchmark. arXiv preprint arXiv:2504.14191, 2025. — [arXiv:2504.14191](https://arxiv.org/abs/2504.14191) find
624. Chen Qu, Liu Yang, Cen Chen, Minghui Qiu, W Bruce Croft, and Mohit Iyyer. Open-retrieval conversational question answering. In Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, pages 539–548, Jul 2020. find
625. Yuxiao Qu, Tianjun Zhang, Naman Garg, and Aviral Kumar. Recursive introspection: Teaching language model agents how to self-improve. Advances in Neural Information Processing Systems, 37: 55249–55285, Dec 2024. find
626. Marissa Radensky, Simra Shahid, Raymond Fok, Pao Siangliulue, Tom Hope, and Daniel S Weld. Scideator: Human-llm scientific idea generation grounded in research-paper facet recombination. arXiv preprint arXiv:2409.14634, 2024. — [arXiv:2409.14634](https://arxiv.org/abs/2409.14634) find
627. Ilija Radosavovic, Tete Xiao, Bike Zhang, Trevor Darrell, Jitendra Malik, and Koushil Sreenath. Real-world humanoid locomotion with reinforcement learning. Science Robotics, 9(89):eadi9579, 2024. find
628. Mohammad Raeini. On the rise of new mathematical spaces and towards ai-driven scientific discovery. Available at SSRN, Mar 2025. find
629. Aditi Raghunathan, Nihar B Shah, et al. Vulnerability of text-matching in ml/ai conference reviewer assignments to collusions. arXiv preprint arXiv:2412.06606, 2024. — [arXiv:2412.06606](https://arxiv.org/abs/2412.06606) find
630. Daking Rai, Yilun Zhou, Shi Feng, Abulhair Saparov, and Ziyu Yao. A practical review of mechanistic interpretability for transformer-based language models. arXiv preprint arXiv:2407.02646, 2024. find
631. Maziar Raissi, Paris Perdikaris, and George E Karniadakis. Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations. Journal of Computational physics, 378:686–707, Feb 2019. find
632. Maziar Raissi, Paris Perdikaris, Nazanin Ahmadi, and George Em Karniadakis. Physics-informed neural networks and extensions. arXiv preprint arXiv:2408.16806, 2024. — [arXiv:2408.16806](https://arxiv.org/abs/2408.16806) find
633. Mahyar Rajabi-Kochi, Negareh Mahboubi, Aseem Partap Singh Gill, and Seyed Mohamad Moosavi. Adaptive representation of molecules and materials in bayesian optimization. Chemical Science, 16 (13):5464–5474, Feb 2025. find
634. Sriram Ranga, Rui Mao, Erik Cambria, and Anupam Chattopadhyay. The plagiarism singularity conjecture. In Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), pages 10245–10255,… find
635. Delip Rao, Jonathan Young, Thomas Dietterich, and Chris Callison-Burch. Withdrarxiv: A large-scale dataset for retraction study. arXiv preprint arXiv:2412.03775, 2024. — [arXiv:2412.03775](https://arxiv.org/abs/2412.03775) find
636. Delip Rao, Weiqiu You, Eric Wong, and Chris Callison-Burch. Nsf-scify: Mining the nsf awards database for scientific claims. arXiv preprint arXiv:2503.08600, 2025.
637. Vishisht Rao, Aounon Kumar, Himabindu Lakkaraju, and Nihar B Shah. Detecting llm-written peer reviews. arXiv preprint arXiv:2503.15772, 2025. — [arXiv:2503.15772](https://arxiv.org/abs/2503.15772) find
638. Md Mahinur Rashid, Hasin Kawsar Jahan, Annysha Huzzat, Riyasaat Ahmed Rahul, Tamim Bin Zakir, Farhana Meem, Md Saddam Hossain Mukta, and Swakkhar Shatabda. Text2chart: A multi-staged chart generator from natural language text. In Pacific-Asia Conference on Knowledge Discovery and Data Mining, pages… find
639. Shaina Raza, Brian Schwartz, and Laura C Rosella. Coquad: a covid-19 question answering dataset system, facilitating research, benchmarking, and practice. BMC bioinformatics, 23(1):210, Jun 2022. find
640. Chandan K Reddy and Parshin Shojaee. Towards scientific discovery with generative ai: Progress, opportunities, and challenges. In Proceedings of the AAAI Conference on Artificial Intelligence, volume 39, pages 28601–28609, Jan 2025. find
641. Tohida Rehman, Debarshi Kumar Sanyal, and Samiran Chattopadhyay. Can pre-trained language models generate titles for research papers? In International Conference on Asian Digital Libraries, pages 154–170. Springer, Dec 2025. find
642. Shuo Ren, Pu Jian, Zhenjiang Ren, Chunlin Leng, Can Xie, and Jiajun Zhang. Towards scientific intelligence: A survey of llm-based scientific agents. arXiv preprint arXiv:2503.24047, 2025. find
643. Jonathan Roberts, Kai Han, Neil Houlsby, and Samuel Albanie. Scifibench: Benchmarking large multimodal models for scientific figure interpretation. arXiv preprint arXiv:2405.08807, 2024. — [arXiv:2405.08807](https://arxiv.org/abs/2405.08807) find
644. Zachary Robertson. Gpt4 is slightly helpful for peer-review assistance: A pilot study. arXiv preprint arXiv:2307.05492, 2023. — [arXiv:2307.05492](https://arxiv.org/abs/2307.05492) find
645. Ambrose Robinson, William Thorne, Ben P Wu, Abdullah Pandor, Munira Essat, Mark Stevenson, and Xingyi Song. Bio-sieve: exploring instruction tuning large language models for systematic review automation. arXiv preprint arXiv:2308.06610, 2023. — [arXiv:2308.06610](https://arxiv.org/abs/2308.06610) find
646. Juan A Rodriguez, David Vazquez, Issam Laradji, Marco Pedersoli, and Pau Rodriguez. Figgen: Text to scientific figure generation. arXiv preprint arXiv:2306.00800, 2023. — [arXiv:2306.00800](https://arxiv.org/abs/2306.00800) find
647. Juan A Rodriguez, Xiangru Jian, Siba Smarak Panigrahi, Tianyu Zhang, Aarash Feizi, Abhay Puri, Akshay Kalkunte Suresh, François Savard, Ahmed Masry, Shravan Nayak, et al. Bigdocs: An open dataset for training multimodal models on document and code tasks. In The Thirteenth International Conference on… find
648. Juan A Rodriguez, Abhay Puri, Shubham Agarwal, Issam H Laradji, Pau Rodriguez, Sai Rajeswar, David Vazquez, Christopher Pal, and Marco Pedersoli. Starvector: Generating scalable vector graphics code from images and text. In Proceedings of the Computer Vision and Pattern Recognition Conference, pages… find
649. D Gordon Rohman. Pre-writing: The stage of discovery in the writing process. College Composition & Communication, 16(2):106–112, May 1965. find
650. Jennifer E Rood, Anna Hupalowska, and Aviv Regev. Toward a foundation model of causal cell and tissue biology with a perturbation cell and tissue atlas. Cell, 187(17):4520–4545, Aug 2024. find
651. Yusuf Roohani, Andrew Lee, Qian Huang, Jian Vora, Zachary Steinhart, Kexin Huang, Alexander Marson, Percy Liang, and Jure Leskovec. Biodiscoveryagent: An ai agent for designing genetic perturbation experiments. arXiv preprint arXiv:2405.17631, 2024. find
652. Emely Rosbach, Jonathan Ganz, Jonas Ammeling, Andreas Riener, and Marc Aubreville. Automation bias in ai-assisted medical decision-making under time pressure in computational pathology. In BVM Workshop, pages 129–134. Springer, Mar 2025. find
653. Zhyar Rzgar K Rostam and Gábor Kertész. Fine-tuning large language models for scientific text classification: A comparative study. In 2024 IEEE 6th International Symposium on Logistics and Industrial Informatics (LINDI), pages 000233–000238. IEEE, Oct 2024. find
654. Tony Rousmaniere, Xu Li, Yimeng Zhang, and Siddharth Shah. Large language models as mental health resources: Patterns of use in the united states, Mar 2025. find
655. Pritam Roy and Dhananjoy Datta. Ai-driven discovery: The transformative impact of machine learning on research and development. In Evolving Landscapes of Research and Development: Trends, Challenges, and Opportunities, pages 29–52. IGI Global Scientific Publishing, Jun 2025. find
656. Sayar Ghosh Roy and Jiawei Han. Ilciter: Evidence-grounded interpretable local citation recommendation. arXiv preprint arXiv:2403.08737, 2024. find
657. Baptiste Roziere, Jonas Gehring, Fabian Gloeckle, Sten Sootla, Itai Gat, Xiaoqing Ellen Tan, Yossi Adi, Jingyu Liu, Romain Sauvestre, Tal Remez, et al. Code llama: Open foundation models for code. arXiv preprint arXiv:2308.12950, 2023.
658. Kai Ruan, Xuan Wang, Jixiang Hong, and Hao Sun. Liveideabench: Evaluating llms’ scientific creativity and idea generation with minimal context. arXiv preprint arXiv:2412.17596, 2024.
659. Yixiang Ruan, Chenyin Lu, Ning Xu, Yuchen He, Yixin Chen, Jian Zhang, Jun Xuan, Jianzhang Pan, Qun Fang, Hanyu Gao, et al. An automatic end-to-end chemical synthesis development platform powered by large language models. Nature communications, 15(1):10160, Nov 2024. find
660. Masoud Jalili Sabet, Philipp Dufter, François Yvon, and Hinrich Schütze. Simalign: High quality word alignments without parallel training data using static and contextualized embeddings. arXiv preprint arXiv:2004.08728, 2020. find
661. Henrik Skaug Sætra. The rise of the research automaton: Science as process or product in the era of generative ai? Available at SSRN 5219722, Apr 2025. find
662. Tanik Saikh, Tirthankar Ghosal, Amish Mittal, Asif Ekbal, and Pushpak Bhattacharyya. Scienceqa: A novel resource for question answering on scholarly articles. International Journal on Digital Libraries, 23(3):289–301, Jul 2022. find
663. Shubhra Kanti Karmaker Santu, Sanjeev Kumar Sinha, Naman Bansal, Alex Knipper, Souvika Sarkar, John Salvador, Yash Mahajan, Sri Guttikonda, Mousumi Akter, Matthew Freestone, et al. Prompting llms to compose meta-review drafts from peer-review narratives of scholarly manuscripts. arXiv preprint arXiv… — [arXiv:2402.15589](https://arxiv.org/abs/2402.15589) find
664. Aishik Sanyal, Samuel Schapiro, Sumuk Shashidhar, Royce Moon, Lav R Varshney, and Dilek Hakkani-Tur. Spark: A system for scientifically creative idea generation. arXiv preprint arXiv:2504.20090, 2025. find
665. Burcu Sayin, Ipek Baris Schlicht, Ngoc Vo Hong, Sara Allievi, Jacopo Staiano, Pasquale Minervini, and Andrea Passerini. Medsyn: Enhancing diagnostics with human-ai collaboration. arXiv preprint arXiv:2506.14774, 2025. — [arXiv:2506.14774](https://arxiv.org/abs/2506.14774) find
666. Timo Schick, Jane Dwivedi-Yu, Roberto Dessì, Roberta Raileanu, Maria Lomeli, Eric Hambro, Luke Zettlemoyer, Nicola Cancedda, and Thomas Scialom. Toolformer: Language models can teach themselves to use tools. Advances in Neural Information Processing Systems, 36:68539–68551, Dec 2023.
667. Emma Schleiger, Claire Mason, Claire Naughtin, Andrew Reeson, and Cecile Paris. Collaborative intelligence: A scoping review of current applications. Applied Artificial Intelligence, 38(1):2327890, Mar 2024. find
668. Samuel Schmidgall and Michael Moor. Agentrxiv: Towards collaborative autonomous research. arXiv preprint arXiv:2503.18102, 2025. find
669. Samuel Schmidgall, Yusheng Su, Ze Wang, Ximeng Sun, Jialian Wu, Xiaodong Yu, Jiang Liu, Zicheng Liu, and Emad Barsoum. Agent laboratory: Using llm agents as research assistants. arXiv preprint arXiv:2501.04227, 2025.
670. Antony Seabra, Claudio Cavalcante, Joao Nepomuceno, Lucas Lago, Nicolaas Ruberg, and Sergio Lifschitz. Dynamic multi-agent orchestration and retrieval for multi-source question-answer systems using large language models. arXiv preprint arXiv:2412.17964, 2024. — [arXiv:2412.17964](https://arxiv.org/abs/2412.17964) find
671. Andrew W Senior, Richard Evans, John Jumper, James Kirkpatrick, Laurent Sifre, Tim Green, Chongli Qin, Augustin Žídek, Alexander WR Nelson, Alex Bridgland, et al. Improved protein structure prediction using potentials from deep learning. Nature, 577(7792):706–710, Jan 2020. find
672. Junpyo Seo, Dongwan Kim, Jaewook Jeong, Inkyu Park, and Junho Min. FlavorDiffusion: Modeling food-chemical interactions with diffusion. In Peter Jansen, Bhavana Dalvi Mishra, Harsh Trivedi, Bodhisattwa Prasad Majumder, Tom Hope, Tushar Khot, Doug Downey, and Eric Horvitz, editors, Proceedings of the… find
673. Sergio A Serrano, Jose Martinez-Carranza, and L Enrique Sucar. Knowledge transfer for cross-domain reinforcement learning: a systematic review. IEEE Access, Jul 2024. find
674. Abdul Shahid, Muhammad Tanvir Afzal, Moloud Abdar, Mohammad Ehsan Basiri, Xujuan Zhou, Neil Y Yen, and Jia-Wei Chang. Insights into relevant knowledge extraction techniques: a comprehensive review. The Journal of Supercomputing, 76:1695–1733, Oct 2020. find
675. Mohamed H Shahin, Srijib Goswami, Sebastian Lobentanzer, and Brian W Corrigan. Agents for change: Artificial intelligent workflows for quantitative clinical pharmacology and translational sciences. Clinical and Translational Science, 18(3):e70188, Mar 2025. find
676. Yijia Shao, Yucheng Jiang, Theodore A Kanell, Peter Xu, Omar Khattab, and Monica S Lam. Assisting in writing wikipedia-like articles from scratch with large language models. arXiv preprint arXiv:2402.14207, 2024.
677. Zachary Sheldon and Peeyush Kumar. Economic anthropology in the era of generative artificial intelligence. arXiv preprint arXiv:2410.15238, 2024. — [arXiv:2410.15238](https://arxiv.org/abs/2410.15238) find
678. Xiang Shi, Jiawei Liu, Yinpeng Liu, Qikai Cheng, and Wei Lu. Every part matters: Integrity verification of scientific figures based on multimodal large language models. arXiv preprint arXiv:2407.18626, 2024. — [arXiv:2407.18626](https://arxiv.org/abs/2407.18626) find
679. Zhengliang Shi, Shen Gao, Zhen Zhang, Xiuying Chen, Zhumin Chen, Pengjie Ren, and Zhaochun Ren. Towards a unified framework for reference retrieval and related work generation. In Findings of the Association for Computational Linguistics: EMNLP 2023, pages 5785–5799, Dec 2023. find
680. Zhengliang Shi, Lingyong Yan, Dawei Yin, Suzan Verberne, Maarten de Rijke, and Zhaochun Ren. Iterative self-incentivization empowers large language models as agentic searchers. arXiv preprint arXiv:2505.20128, 2025. — [arXiv:2505.20128](https://arxiv.org/abs/2505.20128) find
681. Hyungyu Shin, Jingyu Tang, Yoonjoo Lee, Nayoung Kim, Hyunseung Lim, Ji Yong Cho, Hwajung Hong, Moontae Lee, and Juho Kim. Automatically evaluating the paper reviewing capability of large language models. arXiv preprint arXiv:2502.17086, 2025. — [arXiv:2502.17086](https://arxiv.org/abs/2502.17086) find
682. Hyungyu Shin, Jingyu Tang, Yoonjoo Lee, Nayoung Kim, Hyunseung Lim, Ji Yong Cho, Hwajung Hong, Moontae Lee, and Juho Kim. Mind the blind spots: A focus-level evaluation framework for llm reviews. arXiv preprint arXiv:2502.17086, 2025.
683. Noah Shinn, Federico Cassano, Ashwin Gopinath, Karthik Narasimhan, and Shunyu Yao. Reflexion: Language agents with verbal reinforcement learning. Advances in Neural Information Processing Systems, 36:8634–8652, Dec 2023.
684. Parshin Shojaee, Kazem Meidani, Shashank Gupta, Amir Barati Farimani, and Chandan K. Reddy. LLM-SR: Scientific equation discovery via programming with large language models. In The Thirteenth International Conference on Learning Representations, Jan 2025. URL https://openreview.net/ forum?id=m2nmp8P… ↗
685. Parshin Shojaee, Ngoc-Hieu Nguyen, Kazem Meidani, Amir Barati Farimani, Khoa D Doan, and Chandan K Reddy. Llm-srbench: A new benchmark for scientific equation discovery with large language models. arXiv preprint arXiv:2504.10415, 2025. find
686. Parshin Shojaee, Ngoc-Hieu Nguyen, Kazem Meidani, Amir Barati Farimani, Khoa D Doan, and Chandan K. Reddy. LLM-SRBench: A new benchmark for scientific equation discovery with large language models. In Forty-second International Conference on Machine Learning, May 2025. URL https://openreview.net/for… ↗
687. Chenglei Si, Diyi Yang, and Tatsunori Hashimoto. Can llms generate novel research ideas? a large-scale human study with 100+ nlp researchers. arXiv preprint arXiv:2409.04109, 2024.
688. Shoaib Ahmed Siddiqui, Yanzhi Chen, Juyeon Heo, Menglin Xia, and Adrian Weller. On evaluating LLMs’ capabilities as functional approximators: A Bayesian evaluation framework. In Owen Rambow, Leo Wanner, Marianna Apidianaki, Hend Al-Khalifa, Barbara Di Eugenio, and Steven Schockaert, editors, Proceed… find
689. Aditi Singh, Abul Ehtesham, Saket Kumar, and Tala Talaei Khoei. Agentic retrieval-augmented generation: A survey on agentic rag. arXiv preprint arXiv:2501.09136, 2025. — [arXiv:2501.09136](https://arxiv.org/abs/2501.09136) find
690. Amanpreet Singh, Joseph Chee Chang, Chloe Anastasiades, Dany Haddad, Aakanksha Naik, Amber Tanaka, Angele Zamarron, Cecile Nguyen, Jena D Hwang, Jason Dunkleberger, et al. Ai2 scholar qa: Organized literature synthesis with attribution. arXiv preprint arXiv:2504.10861, 2025. find
691. Ashish Singh, Prateek Agarwal, Zixuan Huang, Arpita Singh, Tong Yu, Sungchul Kim, Victor Bursztyn, Nikos Vlassis, and Ryan A Rossi. Figcaps-hf: A figure-to-caption generative framework and benchmark with human feedback. arXiv preprint arXiv:2307.10867, 2023. find
692. Sanjay Singh and Amaresh Chakrabarti. Supporting assessment of novelty of design problems using concept of problem sapphire. arXiv preprint arXiv:2410.18629, 2024. — [arXiv:2410.18629](https://arxiv.org/abs/2410.18629) find
693. Shruti Singh, Mayank Singh, and Pawan Goyal. Compare: a taxonomy and dataset of comparison discussions in peer reviews. In 2021 ACM/IEEE Joint Conference on Digital Libraries (JCDL), pages 238–241. IEEE, Aug 2021. find
694. Shruti Singh, Nandan Sarkar, and Arman Cohan. Scidqa: A deep reading comprehension dataset over scientific papers. arXiv preprint arXiv:2411.05338, 2024. find
695. Karan Singhal, Shekoofeh Azizi, Tao Tu, S. Sara Mahdavi, Jason Wei, Hyung Won Chung, Nathan Scales, Ajay Tanwani, Heather Cole-Lewis, Stephen Pfohl, Perry Payne, Martin Seneviratne, Paul Gamble, Chris Kelly, Abubakr Babiker, Nathanael Schärli, Aakanksha Chowdhery, Philip Mansfield, Dina Demner-Fushm… — Large Language Models Encode Clinical Knowledge
696. Karan Singhal, Tao Tu, Juraj Gottweis, Rory Sayres, Ellery Wulczyn, Mohamed Amin, Le Hou, Kevin Clark, Stephen R Pfohl, Heather Cole-Lewis, et al. Toward expert-level medical question answering with large language models. Nature Medicine, pages 1–8, Jan 2025. find
697. Arnab Sinha, Zhihong Shen, Yang Song, Hao Ma, Darrin Eide, Bo-June Hsu, and Kuansan Wang. An overview of microsoft academic service (mas) and applications. In Proceedings of the 24th international conference on world wide web, pages 243–246, May 2015. find
698. Shiven Sinha, Shashwat Goel, Ponnurangam Kumaraguru, Jonas Geiping, Matthias Bethge, and Ameya Prabhu. Can language models falsify? evaluating algorithmic reasoning with counterexample creation. arXiv preprint arXiv:2502.19414, 2025. — [arXiv:2502.19414](https://arxiv.org/abs/2502.19414) find
699. Michael D Skarlinski, Sam Cox, Jon M Laurent, James D Braza, Michaela Hinks, Michael J Hammerling, Manvitha Ponnapati, Samuel G Rodriques, and Andrew D White. Language agents achieve superhuman synthesis of scientific knowledge. arXiv preprint arXiv:2409.13740, 2024. find
700. Khachik Smbatyan, Tsolak Ghukasyan, Tigran Aghajanyan, Hovhannes Dabaghyan, Sergey Adamyan, Aram Bughdaryan, Vahagn Altunyan, Gagik Navasardyan, Aram Davtyan, Anush Hakobyan, et al. Can ai agents design and implement drug discovery pipelines? arXiv preprint arXiv:2504.19912, 2025. — [arXiv:2504.19912](https://arxiv.org/abs/2504.19912) find
701. IEEE Computer Society. How to make peer review recommendations and decisions. https://www.computer.org/publications/making-peer-review-recommendations. ↗
702. Gleb Vitalevich Solovev, Alina Borisovna Zhidkovskaya, Anastasia Orlova, Anastasia Vepreva, Tonkii Ilya, Rodion Golovinskii, Nina Gubina, Denis Chistiakov, Timur A Aliev, Ivan Poddiakov, et al. Towards llm-driven multi-agent pipeline for drug discovery: Neurodegenerative diseases case study. In 2nd… find
703. Guijin Son, Jiwoo Hong, Honglu Fan, Heejeong Nam, Hyunwoo Ko, Seungwon Lim, Jinyeop Song, Jinha Choi, Gonçalo Paulo, Youngjae Yu, et al. When ai co-scientists fail: Spot-a benchmark for automated verification of scientific research. arXiv preprint arXiv:2505.11855, 2025. find
704. Cuiping Song and Yanping Song. Enhancing academic writing skills and motivation: assessing the efficacy of chatgpt in ai-assisted language learning for efl students. Frontiers in Psychology, 14: 1260843, Dec 2023. find
705. Jinwang Song, Yanxin Song, Guangyu Zhou, Wenhui Fu, Kunli Zhang, and Hongying Zan. Enhancing chinese essay discourse logic evaluation through optimized fine-tuning of large language models. In CCF International Conference on Natural Language Processing and Chinese Computing, pages 342–352. Springer,… find
706. Peiyang Song, Kaiyu Yang, and Anima Anandkumar. Towards large language models as copilots for theorem proving in lean. arXiv preprint arXiv:2404.12534, 2024. find
707. Tao Song, Man Luo, Xiaolong Zhang, Linjiang Chen, Yan Huang, Jiaqi Cao, Qing Zhu, Daobin Liu, Baicheng Zhang, Gang Zou, et al. A multiagent-driven robotic ai chemist enabling autonomous chemical research on demand. Journal of the American Chemical Society, 147(15):12534–12545, Mar 2025. find
708. Yuda Song, Hanlin Zhang, Carson Eisenach, Sham Kakade, Dean Foster, and Udaya Ghai. Mind the gap: Examining the self-improvement capabilities of large language models. arXiv preprint arXiv:2412.02674, 2024. — [arXiv:2412.02674](https://arxiv.org/abs/2412.02674) find
709. Zhilong Song, Minggang Ju, Chunjin Ren, Qiang Li, Chongyi Li, Qionghua Zhou, and Jinlan Wang. Llm-feynman: Leveraging large language models for universal scientific formula and theory discovery. arXiv preprint arXiv:2503.06512, 2025. — [arXiv:2503.06512](https://arxiv.org/abs/2503.06512) find
710. Evan Walter Clark Spotte-Smith. Considering the ethics of large machine learning models in the chemical sciences. Mar 2025. find
711. Henry W Sprueill, Carl Edwards, Khushbu Agarwal, Mariefel V Olarte, Udishnu Sanyal, Conrad Johnston, Hongbin Liu, Heng Ji, and Sutanay Choudhury. Chemreasoner: Heuristic search over a large language model’s knowledge space using quantum-chemical feedback. arXiv preprint arXiv:2402.10980, 2024. find
712. Liana Spytska. The use of artificial intelligence in psychotherapy: development of intelligent therapeutic systems. BMC psychology, 13(1):175, Feb 2025. find
713. Karthik Sreedhar, Alice Cai, Jenny Ma, Jeffrey V Nickerson, and Lydia B Chilton. Simulating cooperative prosocial behavior with multi-agent llms: Evidence and mechanisms for ai agents to inform policy decisions. In Proceedings of the 30th International Conference on Intelligent User Interfaces, page… find
714. Kaustubh Sridhar, Souradeep Dutta, Dinesh Jayaraman, and Insup Lee. Regent: A retrieval-augmented generalist agent that can act in-context in new environments. In NeurIPS 2024 Workshop on Open-World Agents, Dec 2024. find
715. Moritz Staudinger, Wojciech Kusa, Florina Piroi, and Allan Hanbury. An analysis of tasks and datasets in peer reviewing. In Proceedings of the Fourth Workshop on Scholarly Document Processing (SDP 2024), pages 257–268, Aug 2024. find
716. Vaios Stergiopoulos, Michael Vassilakopoulos, Eleni Tousidou, and Antonio Corral. An academic recommender system on large citation data based on clustering, graph modeling and deep learning. Knowledge and Information Systems, 66(8):4463–4496, Apr 2024. find
717. Noy Sternlicht and Tom Hope. Chimera: A knowledge base of idea recombination in scientific literature. arXiv preprint arXiv:2505.20779, 2025. — [arXiv:2505.20779](https://arxiv.org/abs/2505.20779) find
718. Jonathan M Stokes, Kevin Yang, Kyle Swanson, Wengong Jin, Andres Cubillos-Ruiz, Nina M Donghia, Craig R MacNair, Shawn French, Lindsey A Carfrae, Zohar Bloom-Ackermann, et al. A deep learning approach to antibiotic discovery. Cell, 180(4):688–702, Feb 2020. find
719. James W. A. Strachan, Dalila Albergo, Giulia Borghini, Oriana Pansardi, Eugenio Scaliti, Saurabh Gupta, Krati Saxena, Alessandro Rufo, Stefano Panzeri, Guido Manzi, Michael S. A. Graziano, and Cristina Becchio. Testing theory of mind in large language models and humans. Nature Human Behaviour, 8:128… — [doi:10.1038/s41562-024-01895-1](https://doi.org/10.1038/s41562-024-01895-1) find
720. Haoyang Su, Renqi Chen, Shixiang Tang, Xinzhe Zheng, Jingzhe Li, Zhenfei Yin, Wanli Ouyang, and Nanqing Dong. Two heads are better than one: A multi-agent system has the potential to improve scientific idea generation. arXiv preprint arXiv:2410.09403, 2024. — [arXiv:2410.09403](https://arxiv.org/abs/2410.09403) find
721. Yuan Sui, Mengyu Zhou, Mingjie Zhou, Shi Han, and Dongmei Zhang. Table meets llm: Can large language models understand structured table data? a benchmark and empirical study. In Proceedings of the 17th ACM International Conference on Web Search and Data Mining, WSDM ’24, page 645–654, New York, NY,… find
722. Yuan Sui, Mengyu Zhou, Mingjie Zhou, Shi Han, and Dongmei Zhang. Table meets llm: Can large language models understand structured table data? a benchmark and empirical study. In Proceedings of the 17th ACM International Conference on Web Search and Data Mining, pages 645–654, Mar 2024. find
723. Purin Sukpanichnant, Anna Rapberger, and Francesca Toni. Peerarg: Argumentative peer review with llms. arXiv preprint arXiv:2409.16813, 2024. find
724. Bo Sun, Baoxin Wang, Yixuan Wang, Wanxiang Che, Dayong Wu, Shijin Wang, and Ting Liu. Csed: A chinese semantic error diagnosis corpus. arXiv preprint arXiv:2305.05183, 2023. — [arXiv:2305.05183](https://arxiv.org/abs/2305.05183) find
725. Chongyan Sun, Ken Lin, Shiwei Wang, Hulong Wu, Chengfei Fu, and Zhen Wang. Lalaeval: A holistic human evaluation framework for domain-specific large language models. In First Conference on Language Modeling, Aug 2024. find
726. Hao Sun, Yunyi Shen, and Mihaela van der Schaar. Openreview should be protected and leveraged as a community asset for research in the era of large language models. arXiv preprint arXiv:2505.21537, 2025. — [arXiv:2505.21537](https://arxiv.org/abs/2505.21537) find
727. Jiankai Sun, Chuanyang Zheng, Enze Xie, Zhengying Liu, Ruihang Chu, Jianing Qiu, Jiaqi Xu, Mingyu Ding, Hongyang Li, Mengzhe Geng, et al. A survey of reasoning with foundation models. arXiv preprint arXiv:2312.11562, 2023. — [arXiv:2312.11562](https://arxiv.org/abs/2312.11562) find
728. Lu Sun, Stone Tao, Junjie Hu, and Steven P Dow. Metawriter: Exploring the potential and perils of ai writing support in scientific peer review. Proceedings of the ACM on Human-Computer Interaction, 8 (CSCW1):1–32, Apr 2024. find
729. Qiang Sun, Yuanyi Luo, Wenxiao Zhang, Sirui Li, Jichunyang Li, Kai Niu, Xiangrui Kong, and Wei Liu. Docs2kg: A human-llm collaborative approach to unified knowledge graph construction from heterogeneous documents. In Companion Proceedings of the ACM on Web Conference 2025, pages 801–804, May 2025. find
730. Qiushi Sun, Zhoumianze Liu, Chang Ma, Zichen Ding, Fangzhi Xu, Zhangyue Yin, Haiteng Zhao, Zhenyu Wu, Kanzhi Cheng, Zhaoyang Liu, et al. Scienceboard: Evaluating multimodal autonomous agents in realistic scientific workflows. arXiv preprint arXiv:2505.19897, 2025. find
731. Tao Sun, Enhao Pan, Zhengkai Yang, Kaixin Sui, Jiajun Shi, Xianfu Cheng, Tongliang Li, Wenhao Huang, Ge Zhang, Jian Yang, et al. P2p: Automated paper-to-poster generation and fine-grained benchmark. arXiv preprint arXiv:2505.17104, 2025. — [arXiv:2505.17104](https://arxiv.org/abs/2505.17104) find
732. Jayaprakash Sundararaj, Akhil Vyas, and Benjamin Gonzalez-Maldonado. Automated latex code generation from handwritten math expressions using vision transformer. arXiv preprint arXiv:2412.03853, 2024. — [arXiv:2412.03853](https://arxiv.org/abs/2412.03853) find
733. Gaurav Suri, Lily R Slater, Ali Ziaee, and Morgan Nguyen. Do large language models show decision heuristics similar to humans? a case study using gpt-3.5. Journal of Experimental Psychology: General, 153(4):1066, May 2024. find
734. Teo Susnjak, Peter Hwang, Napoleon Reyes, Andre LC Barczak, Timothy McIntosh, and Surangika Ranathunga. Automating research synthesis with domain-specific large language model fine-tuning. ACM Transactions on Knowledge Discovery from Data, 19(3):1–39, Mar 2025. find
735. Kyle Swanson, Wesley Wu, Nash L Bulaong, John E Pak, and James Zou. The virtual lab of ai agents designs new sars-cov-2 nanobodies. Nature, pages 1–3, Aug 2025. find
736. Jaroslaw Szumega, Lamine Bougueroua, Blerina Gkotse, Pierre Jouvelot, and Federico Ravotti. The open review-based (orb) dataset: Towards automatic assessment of scientific papers and experiment proposals in high-energy physics. arXiv preprint arXiv:2312.04576, 2023. — [arXiv:2312.04576](https://arxiv.org/abs/2312.04576) find
737. Nathan J Szymanski, Bernardus Rendy, Yuxing Fei, Rishi E Kumar, Tanjin He, David Milsted, Matthew J McDermott, Max Gallant, Ekin Dogus Cubuk, Amil Merchant, et al. An autonomous laboratory for the accelerated synthesis of novel materials. Nature, 624(7990):86–91, Nov 2023. find
738. Pawin Taechoyotin and Daniel Acuna. Remor: Automated peer review generation with llm reasoning and multi-objective reinforcement learning. arXiv preprint arXiv:2505.11718, 2025. find
739. Pawin Taechoyotin, Guanchao Wang, Tong Zeng, Bradley Sides, and Daniel Acuna. Mamorx: Multi-agent multi-modal scientific review generation with external knowledge. In Neurips 2024 Workshop Foundation Models for Science: Progress, Opportunities, and Challenges, Oct 2024. find
740. Iman Tahamtan, Askar Safipour Afshar, and Khadijeh Ahamdzadeh. Factors affecting number of citations: a comprehensive review of the literature. Scientometrics, 107:1195–1225, Feb 2016. find
741. Sheikh A Tahmid and Gennaro Notomista. Value iteration for learning concurrently executable robotic control tasks. arXiv preprint arXiv:2504.01174, 2025. — [arXiv:2504.01174](https://arxiv.org/abs/2504.01174) find
742. Cheng Tan, Dongxin Lyu, Siyuan Li, Zhangyang Gao, Jingxuan Wei, Siqi Ma, Zicheng Liu, and Stan Z Li. Peer review as a multi-turn and long-context dialogue with role-based interactions. arXiv preprint arXiv:2406.05688, 2024. — [arXiv:2406.05688](https://arxiv.org/abs/2406.05688) find
743. Hongming Tan, Shaoxiong Zhan, Fengwei Jia, Hai-Tao Zheng, and Wai Kin Chan. A hierarchical framework for measuring scientific paper innovation via large language models. arXiv preprint arXiv:2504.14620, 2025. — [arXiv:2504.14620](https://arxiv.org/abs/2504.14620) find
744. Xiangru Tang, Howard Dai, Elizabeth Knight, Fang Wu, Yunyang Li, Tianxiao Li, and Mark Gerstein. A survey of generative ai for de novo drug design: new frontiers in molecule and protein generation. Briefings in Bioinformatics, 25(4):bbae338, Jul 2024. find
745. Xiangru Tang, Xingyao Zhang, Yanjun Shao, Jie Wu, Yilun Zhao, Arman Cohan, Ming Gong, Dongmei Zhang, and Mark Gerstein. Step-back profiling: Distilling user history for personalized scientific writing. arXiv preprint arXiv:2406.14275, 2024. find
746. Zecheng Tang, Keyan Zhou, Juntao Li, Baibei Ji, Jianye Hou, and Min Zhang. L-citeeval: Do long-context models truly leverage context for responding? arXiv preprint arXiv:2410.02115, 2024. — [arXiv:2410.02115](https://arxiv.org/abs/2410.02115) find
747. Gemini Team, Rohan Anil, Sebastian Borgeaud, Jean-Baptiste Alayrac, Jiahui Yu, Radu Soricut, Johan Schalkwyk, Andrew M Dai, Anja Hauth, Katie Millican, et al. Gemini: a family of highly capable multimodal models. arXiv preprint arXiv:2312.11805, 2023.
748. Gemini Team, Petko Georgiev, Ving Ian Lei, Ryan Burnell, Libin Bai, Anmol Gulati, Garrett Tanzer, Damien Vincent, Zhufeng Pan, Shibo Wang, et al. Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context. arXiv preprint arXiv:2403.05530, 2024.
749. Gemma Team, Morgane Riviere, Shreya Pathak, Pier Giuseppe Sessa, Cassidy Hardin, Surya Bhupatiraju, Léonard Hussenot, Thomas Mesnard, Bobak Shahriari, Alexandre Ramé, et al. Gemma 2: Improving open language models at a practical size. arXiv preprint arXiv:2408.00118, 2024. find
750. Illustrae Team. How to create accurate scientific illustrations with ai in 2025. May 2025. URL https://illustrae.co/blog/how-to-create-accurate-scientific-illustrations-ai. ↗
751. Kimi Team, Angang Du, Bofei Gao, Bowei Xing, Changjiu Jiang, Cheng Chen, Cheng Li, Chenjun Xiao, Chenzhuang Du, Chonghua Liao, et al. Kimi k1.5: Scaling reinforcement learning with llms. arXiv preprint arXiv:2501.12599, 2025.
752. NovelSeek Team, Bo Zhang, Shiyang Feng, Xiangchao Yan, Jiakang Yuan, Zhiyin Yu, Xiaohan He, Songtao Huang, Shaowei Hou, Zheng Nie, et al. Novelseek: When agent becomes the scientist–building closed-loop system from hypothesis to verification. arXiv preprint arXiv:2505.16938, 2025. find
753. Qwen Team. Qwq: Reflect deeply on the boundaries of the unknown. https://qwenlm.github.io/blog/qwq-32b-preview/, Dec 2024. Accessed: 2024-12-16. ↗
754. Qwen Team. Qwq-32b: Embracing the power of reinforcement learning, March 2025. URL https://qwenlm.github.io/blog/qwq-32b/. ↗
755. Adrian Tedford. Helping editors find reviewers. https://www.elsevier.com/connect/helping-editors-find-reviewers, Sep 2015. ↗
756. Mike Thelwall and Abdallah Yaghi. Evaluating the predictive capacity of chatgpt for academic peer review outcomes across multiple platforms. Scientometrics, pages 1–23, Mar 2025. find
757. Tingzhong Tian, Shuya Li, Ziting Zhang, Lin Chen, Ziheng Zou, Dan Zhao, and Jianyang Zeng. Benchmarking compound activity prediction for real-world drug discovery applications. Communications Chemistry, 7(1):127, Jun 2024. find
758. Josh Tobin, Rachel Fong, Alex Ray, Jonas Schneider, Wojciech Zaremba, and Pieter Abbeel. Domain randomization for transferring deep neural networks from simulation to the real world. In 2017 IEEE/RSJ international conference on intelligent robots and systems (IROS), pages 23–30. IEEE, 2017. find
759. Gary Tom, Stefan P Schmid, Sterling G Baird, Yang Cao, Kourosh Darvish, Han Hao, Stanley Lo, Sergio Pablo-García, Ella M Rajaonson, Marta Skreta, et al. Self-driving laboratories for chemistry and materials science. Chemical Reviews, 124(16):9633–9732, Aug 2024. find
760. Song Tong, Kai Mao, Zhen Huang, Yukun Zhao, and Kaiping Peng. Automating psychological hypothesis generation with ai: when large language models meet causal graph. Humanities and Social Sciences Communications, 11(1):1–14, Jul 2024. find
761. Alexander Tornede, Difan Deng, Theresa Eimer, Joseph Giovanelli, Aditya Mohan, Tim Ruhkopf, Sarah Segel, Daphne Theodorakopoulos, Tanja Tornede, Henning Wachsmuth, et al. Automl in the age of large language models: Current challenges, future opportunities and risks. arXiv preprint arXiv:2306.08107,… find
762. Vladislav Trifonov, Iaroslav Kononov, Daniil Sherki, Oleg Svidchenko, Aleksei Shpilman, and Ekaterina Muravleva. Ai-powered platform for scientific discovery. In AI4X 2025 International Conference, Jul 2025. find
763. Stacey Truex, Nathalie Baracaldo, Ali Anwar, Thomas Steinke, Heiko Ludwig, Rui Zhang, and Yi Zhou. A hybrid approach to privacy-preserving federated learning. In Proceedings of the 12th ACM workshop on artificial intelligence and security, pages 1–11, Aug 2019. find
764. Joseph Tu, Hilda Hadan, Derrick M Wang, Sabrina A Sgandurra, Reza Hadi Mogavi, and Lennart E Nacke. Augmenting the author: Exploring the potential of ai collaboration in academic writing. arXiv preprint arXiv:2404.16071, 2024. — [arXiv:2404.16071](https://arxiv.org/abs/2404.16071) find
765. Keith Tyser, Ben Segev, Gaston Longhitano, Xin-Yu Zhang, Zachary Meeks, Jason Lee, Uday Garg, Nicholas Belsten, Avi Shporer, Madeleine Udell, et al. Ai-driven review systems: evaluating llms in scalable and bias-aware academic reviews. arXiv preprint arXiv:2408.10365, 2024. find
766. Shiekh Zia Uddin, Sachin Vaidya, Shrish Choudhary, Zhuo Chen, Raafat K Salib, Luke Huang, Dirk R Englund, and Marin Soljačić. Ai-driven robotics for free-space optics. arXiv preprint arXiv:2505.17985, 2025. — [arXiv:2505.17985](https://arxiv.org/abs/2505.17985) find
767. Pietro Vischia. Ai-assisted design of experiments at the frontiers of computation: methods and new perspectives. arXiv preprint arXiv:2501.04448, 2025. — [arXiv:2501.04448](https://arxiv.org/abs/2501.04448) find
768. Juraj Vladika and Florian Matthes. Comparing knowledge sources for open-domain scientific claim verification. arXiv preprint arXiv:2402.02844, 2024. find
769. Juraj Vladika and Florian Matthes. Improving health question answering with reliable and time-aware evidence retrieval. arXiv preprint arXiv:2404.08359, 2024. find
770. Luka Vrečar, Joe Wells, and Fairouz Kamareddine. Towards semantic markup of mathematical documents via user interaction. In International Conference on Intelligent Computer Mathematics, pages 223–240. Springer, Jul 2024. find
771. David Wadden, Kyle Lo, Lucy Lu Wang, Arman Cohan, Iz Beltagy, and Hannaneh Hajishirzi. Multivers: Improving scientific claim verification with weak supervision and full-document context. arXiv preprint arXiv:2112.01640, 2021. find
772. David Wadden, Kejian Shi, Jacob Morrison, Aakanksha Naik, Shruti Singh, Nitzan Barzilay, Kyle Lo, Tom Hope, Luca Soldaini, Zejiang Shen, et al. Sciriff: A resource to enhance language model instruction-following over scientific literature. In Neurips 2024 Workshop Foundation Models for Science: Prog…
773. Byron C Wallace, Sayantan Saha, Frank Soboczenski, and Iain J Marshall. Generating (factual?) narrative summaries of rcts: Experiments with neural multi-document summarization. AMIA Summits on Translational Science Proceedings, 2021:605, May 2021. find
774. Yuwei Wan, Yixuan Liu, Aswathy Ajith, Clara Grazian, Bram Hoex, Wenjie Zhang, Chunyu Kit, Tong Xie, and Ian Foster. Sciqag: A framework for auto-generated science question answering dataset with fine-grained evaluation. arXiv preprint arXiv:2405.09939, 2024. — [arXiv:2405.09939](https://arxiv.org/abs/2405.09939) find
775. Chengshi Wang, Yeon-Ju Kim, Aikaterini Vriza, Rohit Batra, Arun Baskaran, Naisong Shan, Nan Li, Pierre Darancet, Logan Ward, Yuzi Liu, et al. Autonomous platform for solution processing of electronic polymers. Nature communications, 16(1):1498, 2025. find
776. Chengye Wang, Yifei Shen, Zexi Kuang, Arman Cohan, and Yilun Zhao. SciVer: Evaluating foundation models for multimodal scientific claim verification. In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 8562–8579, 2025.
777. Dingzirui Wang, Longxu Dou, and Wanxiang Che. A survey on table-and-text hybridqa: Concepts, methods, challenges and future directions. arXiv preprint arXiv:2212.13465, 2022. — [arXiv:2212.13465](https://arxiv.org/abs/2212.13465) find
778. Dingzirui Wang, Longxu Dou, Xuanliang Zhang, Qingfu Zhu, and Wanxiang Che. Improving demonstration diversity by human-free fusing for text-to-sql. arXiv preprint arXiv:2402.10663, 2024. find
779. Haiming Wang, Huajian Xin, Chuanyang Zheng, Lin Li, Zhengying Liu, Qingxing Cao, Yinya Huang, Jing Xiong, Han Shi, Enze Xie, et al. Lego-prover: Neural theorem proving with growing libraries. arXiv preprint arXiv:2310.00656, 2023. find
780. Haiming Wang, Ye Yuan, Zhengying Liu, Jianhao Shen, Yichun Yin, Jing Xiong, Enze Xie, Han Shi, Yujun Li, Lin Li, et al. Dt-solver: Automated theorem proving with dynamic-tree sampling guided by proof-level value function. In Proceedings of the 61st Annual Meeting of the Association for Computational… find
781. Haiming Wang, Huajian Xin, Zhengying Liu, Wenda Li, Yinya Huang, Jianqiao Lu, Zhicheng Yang, Jing Tang, Jian Yin, Zhenguo Li, et al. Proving theorems recursively. arXiv preprint arXiv:2405.14414, 2024. find
782. Haining Wang. A content-based novelty measure for scholarly publications: A proof of concept. In International Conference on Information, pages 409–420. Springer, Apr 2024. find
783. Hanchen Wang, Tianfan Fu, Yuanqi Du, Wenhao Gao, Kexin Huang, Ziming Liu, Payal Chandak, Shengchao Liu, Peter Van Katwyk, Andreea Deac, et al. Scientific discovery in the age of artificial intelligence. Nature, 620(7972):47–60, Aug 2023. find
784. Hanchen Wang, Yichun He, Paula P Coelho, Matthew Bucci, Abbas Nazir, Bob Chen, Linh Trinh, Serena Zhang, Kexin Huang, Vineethkrishna Chandrasekar, et al. Spatialagent: An autonomous ai agent for spatial biology. bioRxiv, pages 2025–04, Apr 2025. find
785. Haorui Wang, Marta Skreta, Cher-Tian Ser, Wenhao Gao, Lingkai Kong, Felix Strieth-Kalthoff, Chenru Duan, Yuchen Zhuang, Yue Yu, Yanqiao Zhu, et al. Efficient evolutionary search over chemical space with large language models. arXiv preprint arXiv:2406.16976, 2024. — [arXiv:2406.16976](https://arxiv.org/abs/2406.16976) find
786. Haoyu Wang, Yujia Fu, Zhu Zhang, Shuo Wang, Zirui Ren, Xiaorong Wang, Zhili Li, Chaoqun He, Bo An, Zhiyuan Liu, et al. Llm × mapreduce-v2: Entropy-driven convolutional test-time scaling for generating long-form articles from extremely long resources. arXiv preprint arXiv:2504.05732, 2025. — [arXiv:2504.05732](https://arxiv.org/abs/2504.05732) find
787. Izia Xiaoxiao Wang, Xihan Wu, Edith Coates, Min Zeng, Jiexin Kuang, Siliang Liu, Mengyang Qiu, and Jungyeul Park. Neural automated writing evaluation with corrective feedback. arXiv preprint arXiv:2402.17613, 2024. — [arXiv:2402.17613](https://arxiv.org/abs/2402.17613) find
788. Jiashuo Wang, Yang Xiao, Yanran Li, Changhe Song, Chunpu Xu, Chenhao Tan, and Wenjie Li. Towards a client-centered assessment of llm therapists by client simulation. arXiv preprint arXiv:2406.12266, 2024. — [arXiv:2406.12266](https://arxiv.org/abs/2406.12266) find
789. Lei Wang, Yi Hu, Jiabang He, Xing Xu, Ning Liu, Hui Liu, and Heng Tao Shen. T-sciq: Teaching multimodal chain-of-thought reasoning via mixed large language model signals for science question answering. arXiv preprint arXiv:2305.03453, 2023. find
790. Linghe Wang, Minhwa Lee, Ross Volkov, Luan Tuyen Chau, and Dongyeop Kang. Scholawrite: A dataset of end-to-end scholarly writing process. arXiv preprint arXiv:2502.02904, 2025. — [arXiv:2502.02904](https://arxiv.org/abs/2502.02904) find
791. Lucy Lu Wang, Jay DeYoung, and Byron Wallace. Overview of mslr2022: A shared task on multi-document summarization for literature reviews. In Proceedings of the third workshop on scholarly document processing, Oct 2022. find
792. Pancheng Wang, Shasha Li, Haifang Zhou, Jintao Tang, and Ting Wang. Toc-rwg: Explore the combination of topic model and citation information for automatic related work generation. Ieee Access, 8:13043–13055, Dec 2019. find
793. Pancheng Wang, Shasha Li, Kunyuan Pang, Liangliang He, Dong Li, Jintao Tang, and Ting Wang. Multi-document scientific summarization from a knowledge graph-centric view. arXiv preprint arXiv:2209.04319, 2022. find
794. Pancheng Wang, Shasha Li, Dong Li, Kehan Long, Jintao Tang, and Ting Wang. Disentangling instructive information from ranked multiple candidates for multi-document scientific summarization. In Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retri… find
795. Peng Wang, Yongheng Zhang, Hao Fei, Qiguang Chen, Yukai Wang, Jiasheng Si, Wenpeng Lu, Min Li, and Libo Qin. S3 agent: Unlocking the power of vllm for zero-shot multi-modal sarcasm detection. ACM Transactions on Multimedia Computing, Communications and Applications, Aug 2024. find
796. Peng Wang, Ruihan Tao, Qiguang Chen, Mengkang Hu, and Libo Qin. X-webagentbench: A multilingual interactive web benchmark for evaluating global agentic system. arXiv preprint arXiv:2505.15372, 2025. find
797. Qingyun Wang, Doug Downey, Heng Ji, and Tom Hope. Scimon: Scientific inspiration machines optimized for novelty. In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 279–299, Aug 2024. find
798. Runxiang Wang, Boxiao Wang, Kai Li, Yifan Zhang, and Jian Cheng. Drsr: Llm based scientific equation discovery with dual reasoning from data and experience. arXiv preprint arXiv:2506.04282, 2025. find
799. Siyuan Wang, James R Foulds, Md Osman Gani, and Shimei Pan. Llm-based corroborating and refuting evidence retrieval for scientific claim verification. arXiv preprint arXiv:2503.07937, 2025. — [arXiv:2503.07937](https://arxiv.org/abs/2503.07937) find
800. Wenxiao Wang, Lihui Gu, Liye Zhang, Yunxiang Luo, Yi Dai, Chen Shen, Liang Xie, Binbin Lin, Xiaofei He, and Jieping Ye. Scipip: An llm-based scientific paper idea proposer. arXiv preprint arXiv:2410.23166, 2024. — [arXiv:2410.23166](https://arxiv.org/abs/2410.23166) find
801. Wenxuan Wang, Zizhan Ma, Zheng Wang, Chenghan Wu, Wenting Chen, Xiang Li, and Yixuan Yuan. A survey of llm-based agents in medicine: How far are we from baymax? arXiv preprint arXiv:2502.11211, 2025. find
802. Xiao Wang, Mengjue Tan, Qiao Jin, Guangzhi Xiong, Yu Hu, Aidong Zhang, Zhiyong Lu, and Minjia Zhang. Medcite: Can language models generate verifiable text for medicine? arXiv preprint arXiv:2506.06605, 2025. find
803. Xiaoxuan Wang, Ziniu Hu, Pan Lu, Yanqiao Zhu, Jieyu Zhang, Satyen Subramaniam, Arjun R Loomba, Shichang Zhang, Yizhou Sun, and Wei Wang. Scibench: Evaluating college-level scientific problem-solving abilities of large language models. arXiv preprint arXiv:2307.10635, 2023.
804. Xingyao Wang, Boxuan Li, Yufan Song, Frank F Xu, Xiangru Tang, Mingchen Zhuge, Jiayi Pan, Yueqi Song, Bowen Li, Jaskirat Singh, et al. Opendevin: An open platform for ai software developers as generalist agents. arXiv preprint arXiv:2407.16741, 2024.
805. Xingyao Wang, Boxuan Li, Yufan Song, Frank F Xu, Xiangru Tang, Mingchen Zhuge, Jiayi Pan, Yueqi Song, Bowen Li, Jaskirat Singh, et al. Openhands: An open platform for ai software developers as generalist agents. arXiv preprint arXiv:2407.16741, 2024.
806. Yao Wang, Mingxuan Cui, and Arthur Jiang. Enabling ai scientists to recognize innovation: A domain-agnostic algorithm for assessing novelty. arXiv preprint arXiv:2503.01508, 2025. — [arXiv:2503.01508](https://arxiv.org/abs/2503.01508) find
807. Yidong Wang, Qi Guo, Wenjin Yao, Hongbo Zhang, Xin Zhang, Zhen Wu, Meishan Zhang, Xinyu Dai, Qingsong Wen, Wei Ye, et al. Autosurvey: Large language models can automatically write surveys. Advances in Neural Information Processing Systems, 37:115119–115145, Dec 2024. find
808. Yifan Wang, David Stevens, Pranay Shah, Wenwen Jiang, Miao Liu, Xu Chen, Robert Kuo, Na Li, Boying Gong, Daniel Lee, et al. Model-in-the-loop (milo): Accelerating multimodal ai data annotation with llms. arXiv preprint arXiv:2409.10702, 2024. — [arXiv:2409.10702](https://arxiv.org/abs/2409.10702) find
809. Yixuan Wang, Baoxin Wang, Yijun Liu, Dayong Wu, and Wanxiang Che. Lm-combiner: A contextual rewriting model for chinese grammatical error correction. arXiv preprint arXiv:2403.17413, 2024. find
810. Yixuan Wang, Baoxin Wang, Yijun Liu, Qingfu Zhu, Dayong Wu, and Wanxiang Che. Improving grammatical error correction via contextual data augmentation. arXiv preprint arXiv:2406.17456, 2024. find
811. Yizheng Wang, Jinshuai Bai, Zhongya Lin, Qimin Wang, Cosmin Anitescu, Jia Sun, Mohammad Sadegh Eshaghi, Yuantong Gu, Xi-Qiao Feng, Xiaoying Zhuang, et al. Artificial intelligence for partial differential equations in computational mechanics: A review. arXiv preprint arXiv:2410.19843, 2024. — [arXiv:2410.19843](https://arxiv.org/abs/2410.19843) find
812. Yongzhen Wang, Xiaozhong Liu, and Zheng Gao. Neural related work summarization with a joint context-driven attention mechanism. arXiv preprint arXiv:1901.09492, 2019. find
813. Yubo Wang, Xueguang Ma, Ping Nie, Huaye Zeng, Zhiheng Lyu, Yuxuan Zhang, Benjamin Schneider, Yi Lu, Xiang Yue, and Wenhu Chen. Scholarcopilot: Training large language models for academic writing with accurate citations. arXiv preprint arXiv:2504.00824, 2025. — [arXiv:2504.00824](https://arxiv.org/abs/2504.00824) find
814. Zifeng Wang, Benjamin Danek, and Jimeng Sun. Biodsa-1k: Benchmarking data science agents for biomedical research. arXiv preprint arXiv:2505.16100, 2025. — [arXiv:2505.16100](https://arxiv.org/abs/2505.16100) find
815. Zilong Wang, Hao Zhang, Chun-Liang Li, Julian Martin Eisenschlos, Vincent Perot, Zifeng Wang, Lesly Miculicich, Yasuhisa Fujii, Jingbo Shang, Chen-Yu Lee, et al. Chain-of-table: Evolving tables in the reasoning chain for table understanding. In The Twelfth International Conference on Learning Repres… find
816. Ziqi Wang, Le Hou, Tianjian Lu, Yuexin Wu, Yunxuan Li, Hongkun Yu, and Heng Ji. Enabling language models to implicitly learn self-improvement. arXiv preprint arXiv:2310.00898, 2023. — [arXiv:2310.00898](https://arxiv.org/abs/2310.00898) find
817. Zirui Wang, Mengzhou Xia, Luxi He, Howard Chen, Yitao Liu, Richard Zhu, Kaiqu Liang, Xindi Wu, Haotian Liu, Sadhika Malladi, Alexis Chevalier, Sanjeev Arora, and Danqi Chen. Charxiv: Charting gaps in realistic chart understanding in multimodal llms. In A. Globerson, L. Mackey, D. Belgrave, A. Fan, U… find
818. William Watson and Lawrence Yong. Directed criteria citation recommendation and ranking through link prediction. arXiv preprint arXiv:2403.18855, 2024. — [arXiv:2403.18855](https://arxiv.org/abs/2403.18855) find
819. Jane Webster and Richard T Watson. Analyzing the past to prepare for the future: Writing a literature review. MIS quarterly, pages xiii–xxiii, Jun 2002. find
820. Jason Wei, Zhiqing Sun, Spencer Papay, Scott McKinney, Jeffrey Han, Isa Fulford, Hyung Won Chung, Alex Tachard Passos, William Fedus, and Amelia Glaese. Browsecomp: A simple yet challenging benchmark for browsing agents. arXiv preprint arXiv:2504.12516, 2025. find
821. Haomin Wen, Zhenjie Wei, Yan Lin, Jiyuan Wang, Yuxuan Liang, and Huaiyu Wan. Overleafcopilot: Empowering academic writing in overleaf with large language models. arXiv preprint arXiv:2403.09733, 2024. — [arXiv:2403.09733](https://arxiv.org/abs/2403.09733) find
822. Jiaxin Wen, Chenglei Si, Yueh-han Chen, He He, and Shi Feng. Predicting empirical ai research outcomes with language models. arXiv preprint arXiv:2506.00794, 2025. — [arXiv:2506.00794](https://arxiv.org/abs/2506.00794) find
823. Ju Wen and Lan Yi. Are plain language summaries more readable than scientific abstracts? evidence from six biomedical and life sciences journals. Public Understanding of Science, 34(1):114–126, May 2025. find
824. Yingting Wen and Sandra Laporte. Experiential narratives in marketing: A comparison of generative ai and human content. Journal of Public Policy & Marketing, 44(3):392–410, Oct 2025. doi: 10.1177/ 07439156241297973. URL https://doi.org/10.1177/07439156241297973. — [doi:10.1177/07439156241297973](https://doi.org/10.1177/07439156241297973) ↗
825. Yixuan Weng, Minjun Zhu, Guangsheng Bao, Hongbo Zhang, Jindong Wang, Yue Zhang, and Linyi Yang. Cycleresearcher: Improving automated research via automated review. arXiv preprint arXiv:2411.00816, 2024. find
826. Nicole E Wheeler. Responsible ai in biotechnology: balancing discovery, innovation and biosecurity risks. Frontiers in Bioengineering and Biotechnology, 13:1537471, Feb 2025. find
827. Dustin Wright and Isabelle Augenstein. Citeworth: Cite-worthiness detection for improved scientific document understanding. In Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, pages 1796–1807, May 2021. find
828. Chaoyi Wu, Jiayu Lei, Qiaoyu Zheng, Weike Zhao, Weixiong Lin, Xiaoman Zhang, Xiao Zhou, Ziheng Zhao, Ya Zhang, Yanfeng Wang, et al. Can gpt-4v (ision) serve medical applications? case studies on gpt-4v for multimodal medical diagnosis. arXiv preprint arXiv:2310.09909, Oct 2023. — [arXiv:2310.09909](https://arxiv.org/abs/2310.09909) find
829. Jialong Wu, Baixuan Li, Runnan Fang, Wenbiao Yin, Liwen Zhang, Zhengwei Tao, Dingchu Zhang, Zekun Xi, Yong Jiang, Pengjun Xie, et al. Webdancer: Towards autonomous information seeking agency. arXiv preprint arXiv:2505.22648, 2025.
830. Jian Wu, Jiayu Zhang, Dongyuan Li, Linyi Yang, Aoxiao Zhong, Renhe Jiang, Qingsong Wen, and Yue Zhang. Lag: Llm agents for leaderboard auto generation on demanding. arXiv preprint arXiv:2502.18209, 2025. — [arXiv:2502.18209](https://arxiv.org/abs/2502.18209) find
831. Jinxuan Wu, Wenhan Chao, Xian Zhou, and Zhunchen Luo. Characterizing and verifying scientific claims: Qualitative causal structure is all you need. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pages 13428–13439, Dec 2023. find
832. Junfeng Wu, Jing He, Hai Liu, Zhaoqi Zheng, Yichen Cao, Xingguo Chen, Bingjie Zou, Ruiping Zou, Guohua Zhou, David Sturgess, et al. From literature to lab: Hardware-independent autonomous chemical synthesis with reinforcement learning. In Companion Proceedings of the ACM on Web Conference 2025, page… find
833. Shican Wu, Xiao Ma, Dehui Luo, Lulu Li, Xiangcheng Shi, Xin Chang, Xiaoyun Lin, Ran Luo, Chunlei Pei, Changying Du, et al. Automated review generation method based on large language models. arXiv preprint arXiv:2407.20906, 2024. find
834. Siyang Wu, Honglin Bao, Nadav Kunievsky, and James A Evans. Introspective growth: Automatically advancing llm expertise in technology judgment. arXiv preprint arXiv:2505.12452, 2025. — [arXiv:2505.12452](https://arxiv.org/abs/2505.12452) find
835. Siyuan Wu, Leong Hou U, Sourav S Bhowmick, and Wolfgang Gatterbauer. Pistis: A conflict of interest declaration and detection system for peer review management. In Proceedings of the 2018 International Conference on Management of Data, pages 1713–1716, May 2018. find
836. Wenqing Wu, Chengzhi Zhang, Tong Bao, and Yi Zhao. Sc4anm: Identifying optimal section combinations for automated novelty prediction in academic papers. Expert Systems with Applications, page 126778, May 2025. find
837. Xianjie Wu, Jian Yang, Linzheng Chai, Ge Zhang, Jiaheng Liu, Xeron Du, Di Liang, Daixin Shu, Xianfu Cheng, Tianzhen Sun, et al. Tablebench: A comprehensive and complex benchmark for table question answering. In Proceedings of the AAAI Conference on Artificial Intelligence, volume 39, pages 25497–255… find
838. Yushuai Wu, Ting Zhang, Hao Zhou, Hainan Wu, Hanwen Sunchu, Lei Hu, Xiaofang Chen, Suyuan Zhao, Gaochao Liu, Chao Sun, et al. Deepcre: Transforming drug r&d via ai-driven cross-drug response evaluation. arXiv preprint arXiv:2403.03768, 2024. — [arXiv:2403.03768](https://arxiv.org/abs/2403.03768) find
839. Amelie Wührl, Yarik Menchaca Resendiz, Lara Grimminger, and Roman Klinger. What makes medical claims (un) verifiable? analyzing entity and relation properties for fact verification. arXiv preprint arXiv:2402.01360, 2024. find
840. Amelie Wührl, Dustin Wright, Roman Klinger, and Isabelle Augenstein. Understanding fine-grained distortions in reports of scientific findings. arXiv preprint arXiv:2402.12431, 2024. find
841. X.AI. Grok-2 beta release. https://x.ai/blog/grok-2, Dec 2024. Accessed: 2024-12-16. ↗
842. Renqiu Xia, Bo Zhang, Hancheng Ye, Xiangchao Yan, Qi Liu, Hongbin Zhou, Zijun Chen, Peng Ye, Min Dou, Botian Shi, et al. Chartx & chartvlm: A versatile benchmark and foundation model for complicated chart reasoning. arXiv preprint arXiv:2402.12185, 2024. — [arXiv:2402.12185](https://arxiv.org/abs/2402.12185) find
843. Yutong Xia, Ao Qu, Yunhan Zheng, Yihong Tang, Dingyi Zhuang, Yuxuan Liang, Shenhao Wang, Cathy Wu, Lijun Sun, Roger Zimmermann, et al. Reimagining urban science: Scaling causal inference with large language models. arXiv preprint arXiv:2504.12345, 2025. — [arXiv:2504.12345](https://arxiv.org/abs/2504.12345) find
844. Yanzheng Xiang, Hanqi Yan, Shuyin Ouyang, Lin Gui, and Yulan He. Scireplicate-bench: Benchmarking llms in agent-driven algorithmic reproduction from research papers. arXiv preprint arXiv:2504.00255, 2025. find
845. Yihang Xiao, Jinyi Liu, Yan Zheng, Xiaohan Xie, Jianye Hao, Mingzhi Li, Ruitao Wang, Fei Ni, Yuxiao Li, Jintian Luo, et al. Cellagent: An llm-driven multi-agent framework for automated single-cell data analysis. arXiv preprint arXiv:2407.09811, 2024. — [arXiv:2407.09811](https://arxiv.org/abs/2407.09811) find
846. Huajian Xin, Daya Guo, Zhihong Shao, Zhizhou Ren, Qihao Zhu, Bo Liu, Chong Ruan, Wenda Li, and Xiaodan Liang. Deepseek-prover: Advancing theorem proving in llms through large-scale synthetic data. arXiv preprint arXiv:2405.14333, 2024.
847. Junjie Xing, Yeye He, Mengyu Zhou, Haoyu Dong, Shi Han, Dongmei Zhang, and Surajit Chaudhuri. Table-llm-specialist: Language model specialists for tables using iterative generator-validator fine-tuning. arXiv preprint arXiv:2410.12164, 2024. — [arXiv:2410.12164](https://arxiv.org/abs/2410.12164) find
848. Guangzhi Xiong, Eric Xie, Corey Williams, Myles Kim, Amir Hassan Shariatmadari, Sikun Guo, Stefan Bekiranov, and Aidong Zhang. Toward reliable biomedical hypothesis generation: Evaluating truthfulness and hallucination in large language models. arXiv preprint arXiv:2505.14599, 2025. — [arXiv:2505.14599](https://arxiv.org/abs/2505.14599) find
849. Ruibin Xiong, Yimeng Chen, Dmitrii Khizbullin, Mingchen Zhuge, and Jürgen Schmidhuber. Beyond outlining: Heterogeneous recursive planning for adaptive long-form writing with language models. arXiv preprint arXiv:2503.08275, 2025.
850. Wanghan Xu, Xiangyu Zhao, Yuhao Zhou, Xiaoyu Yue, Ben Fei, Fenghua Ling, Wenlong Zhang, and Lei Bai. Earthse: A benchmark evaluating earth scientific exploration capability for large language models. arXiv preprint arXiv:2505.17139, 2025. — [arXiv:2505.17139](https://arxiv.org/abs/2505.17139) find
851. Zhenran Xu, Senbao Shi, Baotian Hu, Jindi Yu, Dongfang Li, Min Zhang, and Yuxiang Wu. Towards reasoning in large language models via multi-agent peer review collaboration. arXiv preprint arXiv:2311.08152, 2023.
852. Ziyang Xu. Patterns and purposes: A cross-journal analysis of ai tool usage in academic writing. arXiv preprint arXiv:2502.00632, 2025. — [arXiv:2502.00632](https://arxiv.org/abs/2502.00632) find
853. Kevin G Yager. Towards a science exocortex. Digital Discovery, 3(10):1933–1957, Aug 2024. find
854. Yutaro Yamada, Robert Tjarko Lange, Cong Lu, Shengran Hu, Chris Lu, Jakob Foerster, Jeff Clune, and David Ha. The ai scientist-v2: Workshop-level automated scientific discovery via agentic tree search. arXiv preprint arXiv:2504.08066, 2025.
855. Xiangchao Yan, Shiyang Feng, Jiakang Yuan, Renqiu Xia, Bin Wang, Bo Zhang, and Lei Bai. Surveyforge: On the outline heuristics, memory-driven generation, and multi-dimensional evaluation for automated survey writing. arXiv preprint arXiv:2503.04629, 2025.
856. Yibo Yan, Shen Wang, Jiahao Huo, Jingheng Ye, Zhendong Chu, Xuming Hu, Philip S Yu, Carla Gomes, Bart Selman, and Qingsong Wen. Position: Multimodal large language models can significantly advance scientific reasoning. arXiv preprint arXiv:2502.02871, 2025. find
857. An Yang, Baosong Yang, Beichen Zhang, Binyuan Hui, Bo Zheng, Bowen Yu, Chengyuan Li, Dayiheng Liu, Fei Huang, Haoran Wei, Huan Lin, Jian Yang, Jianhong Tu, Jianwei Zhang, Jianxin Yang, Jiaxi Yang, Jingren Zhou, Junyang Lin, Kai Dang, Keming Lu, Keqin Bao, Kexin Yang, Le Yu, Mei Li, Mingfeng Xue, Pei… find
858. Hsin-Jung Yang, Mahsa Khosravi, Benjamin Walt, Girish Krishnan, and Soumik Sarkar. Zero-shot sim-to-real transfer for reinforcement learning-based visual servoing of soft continuum arms. arXiv preprint arXiv:2504.16916, 2025. — [arXiv:2504.16916](https://arxiv.org/abs/2504.16916) find
859. Jianke Yang, Manu Bhat, Bryan Hu, Yadi Cao, Nima Dehmamy, Robin Walters, and Rose Yu. Discovering symbolic differential equations with symmetry invariants. arXiv preprint arXiv:2505.12083, 2025. — [arXiv:2505.12083](https://arxiv.org/abs/2505.12083) find
860. John Jeongseok Yang and Sang-Hyun Hwang. Transforming hematological research documentation with large language models: an approach to scientific writing and data analysis. Blood research, 60 (1):1–11, Mar 2025. find
861. Lin Yang, Shawn Xu, Andrew Sellergren, Timo Kohlberger, Yuchen Zhou, Ira Ktena, Atilla Kiraly, Faruk Ahmed, Farhad Hormozdiari, Tiam Jaroensri, et al. Advancing multimodal medical capabilities of gemini. arXiv preprint arXiv:2405.03162, 2024. — [arXiv:2405.03162](https://arxiv.org/abs/2405.03162) find
862. Rui Yang, Boming Yang, Aosong Feng, Sixun Ouyang, Moritz Blum, Tianwei She, Yuang Jiang, Freddy Lecue, Jinghui Lu, and Irene Li. Graphusion: a rag framework for knowledge graph construction with a global perspective. arXiv preprint arXiv:2410.17600, 2024. — [arXiv:2410.17600](https://arxiv.org/abs/2410.17600) find
863. Yifei Yang, Runhan Shi, Zuchao Li, Shu Jiang, Yang Yang, Bao-Liang Lu, and Hai Zhao. Batgpt-chem: A foundation large model for chemical engineering. Apr 2024. find
864. Yue Yang, MingKang Chen, Qihua Liu, Mengkang Hu, Qiguang Chen, Gengrui Zhang, Shuyue Hu, Guangtao Zhai, Yu Qiao, Yu Wang, et al. Truly assessing fluid intelligence of large language models through dynamic reasoning evaluation. arXiv preprint arXiv:2506.02648, 2025. — [arXiv:2506.02648](https://arxiv.org/abs/2506.02648) find
865. Zhaorui Yang, Bo Pan, Han Wang, Yiyao Wang, Xingyu Liu, Minfeng Zhu, Bo Zhang, and Wei Chen. Multimodal deepresearcher: Generating text-chart interleaved reports from scratch with agentic framework. arXiv preprint arXiv:2506.02454, 2025. — [arXiv:2506.02454](https://arxiv.org/abs/2506.02454) find
866. Zonglin Yang, Xinya Du, Junxian Li, Jie Zheng, Soujanya Poria, and Erik Cambria. Large language models for automated open-domain scientific hypotheses discovery. arXiv preprint arXiv:2309.02726, 2023. find
867. Zonglin Yang, Wanhao Liu, Ben Gao, Tong Xie, Yuqiang Li, Wanli Ouyang, Soujanya Poria, Erik Cambria, and Dongzhan Zhou. MOOSE-chem: Large language models for rediscovering unseen chemistry scientific hypotheses. In The Thirteenth International Conference on Learning Representations, Jan 2025. URL ht… find
868. Zukang Yang, Zixuan Zhu, and Jennifer Zhu. Curiousllm: Elevating multi-document question answering with llm-enhanced knowledge graph reasoning. In Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (… find
869. Nicolas Yax, Hernán Anlló, and Stefano Palminteri. Studying and improving reasoning in humans and machines. Communications Psychology, 2(1):51, Jun 2024. find
870. Mang Ye, Xiuwen Fang, Bo Du, Pong C Yuen, and Dacheng Tao. Heterogeneous federated learning: State-of-the-art and research challenges. ACM Computing Surveys, 56(3):1–44, Oct 2023. find
871. Rui Ye, Xianghe Pang, Jingyi Chai, Jiaao Chen, Zhenfei Yin, Zhen Xiang, Xiaowen Dong, Jing Shao, and Siheng Chen. Are we there yet? revealing the risks of utilizing large language models in scholarly peer review. arXiv preprint arXiv:2412.01708, 2024. find
872. Yanpeng Ye, Jie Ren, Shaozhou Wang, Yuwei Wan, Imran Razzak, Bram Hoex, Haofen Wang, Tong Xie, and Wenjie Zhang. Construction and application of materials knowledge graph in multidisciplinary materials science via large language model. Advances in Neural Information Processing Systems, 37: 56878–568… find
873. Ho Yin, Ting-Yao Hsu, Jiyoo Min, Sungchul Kim, Ryan A Rossi, Tong Yu, Hyunggu Jung, Ting-Hao’Kenneth’ Huang, et al. Understanding how paper writers use ai-generated captions in figure caption writing. arXiv preprint arXiv:2501.06317, 2025. — [arXiv:2501.06317](https://arxiv.org/abs/2501.06317) find
874. Ming Yin, Yuanhao Qu, Dyllan Liu, Ling Yang, Le Cong, and Mengdi Wang. Genome-bench: A scientific reasoning benchmark from real-world expert discussions. bioRxiv, pages 2025–06, 2025. find
875. Chengzhang Yu, Yiming Zhang, Zhixin Liu, Zenghui Ding, Yining Sun, and Zhanpeng Jin. Frame: Feedback-refined agent methodology for enhancing medical research insights. arXiv preprint arXiv:2505.04649, 2025. find
876. Fei Yu, Hongbo Zhang, Prayag Tiwari, and Benyou Wang. Natural language reasoning, a survey. ACM Comput. Surv., 56(12), October 2024. ISSN 0360-0300. doi: 10.1145/3664194. URL https://doi.org/10.1145/3664194. ↗
877. Haofei Yu, Zhaochen Hong, Zirui Cheng, Kunlun Zhu, Keyang Xuan, Jinwei Yao, Tao Feng, and Jiaxuan You. Researchtown: Simulator of human research community. arXiv preprint arXiv:2412.17767, 2024.
878. Hengjie Yu and Yaochu Jin. Unlocking the potential of ai researchers in scientific discovery: What is missing? arXiv preprint arXiv:2503.05822, 2025. — [arXiv:2503.05822](https://arxiv.org/abs/2503.05822) find
879. Jianxiang Yu, Jiaqi Tan, Zichen Ding, Jiapeng Zhu, Jiahao Li, Yao Cheng, Qier Cui, Yunshi Lan, and Xiang Li. Seagraph: Unveiling the whole story of paper review comments. arXiv preprint arXiv:2412.11939, 2024. find
880. Jing Yu, Yuqi Tang, Kehua Feng, Mingyang Rao, Lei Liang, Zhiqiang Zhang, Mengshu Sun, Wen Zhang, Qiang Zhang, Keyan Ding, et al. Scicueval: A comprehensive dataset for evaluating scientific context understanding in large language models. arXiv preprint arXiv:2505.15094, 2025. — [arXiv:2505.15094](https://arxiv.org/abs/2505.15094) find
881. Luyao Yu, Qi Zhang, Chongyang Shi, An Lao, and Liang Xiao. Reinforced subject-aware graph neural network for related work generation. In International Conference on Knowledge Science, Engineering and Management, pages 201–213. Springer, Jul 2024. find
882. Sungduk Yu, Man Luo, Avinash Madasu, Vasudev Lal, and Phillip Howard. Is your paper being reviewed by an llm? investigating ai text detectability in peer review. arXiv preprint arXiv:2410.03019, 2024. find
883. Jiakang Yuan, Xiangchao Yan, Botian Shi, Tao Chen, Wanli Ouyang, Bo Zhang, Lei Bai, Yu Qiao, and Bowen Zhou. Dolphin: Closed-loop open-ended auto-research through thinking, practice, and feedback. arXiv preprint arXiv:2501.03916, 2025. find
884. Shuzhou Yuan and Michael Färber. Hallucinations can improve large language models in drug discovery. arXiv preprint arXiv:2501.13824, 2025. — [arXiv:2501.13824](https://arxiv.org/abs/2501.13824) find
885. Weizhe Yuan and Pengfei Liu. Kid-review: knowledge-guided scientific review generation with oracle pre-training. In Proceedings of the AAAI Conference on Artificial Intelligence, volume 36, pages 11639–11647, Jun 2022. find
886. Weizhe Yuan, Pengfei Liu, and Graham Neubig. Can we automate scientific reviewing? Journal of Artificial Intelligence Research, 75:171–212, Sep 2022. find
887. Wenhao Yuan, Guangyao Chen, Zhilong Wang, and Fengqi You. Empowering generalist material intelligence with large language models. Advanced Materials, page 2502771, May 2025. find
888. Ling Yue, Nithin Somasekharan, Yadi Cao, and Shaowu Pan. Foam-agent: Towards automated intelligent cfd workflows. arXiv preprint arXiv:2505.04997, 2025. — [arXiv:2505.04997](https://arxiv.org/abs/2505.04997) find
889. Miguel Zabaleta and Joel Lehman. Simulating tabular datasets through llms to rapidly explore hypotheses about real-world entities. arXiv preprint arXiv:2411.18071, 2024. — [arXiv:2411.18071](https://arxiv.org/abs/2411.18071) find
890. César Zamudio, Jamie L Grigsby, and Meg Michelsen. Raise: A new method to develop experimental stimuli for advertising research with image generative artificial intelligence. Journal of Advertising, pages 1–16, Jan 2024. find
891. Fengzhu Zeng and Wei Gao. Prompt to be consistent is better than self-consistent? few-shot and zero-shot fact verification with pre-trained language models. arXiv preprint arXiv:2306.02569, 2023. find
892. Qi Zeng, Mankeerat Sidhu, Hou Pong Chan, Lu Wang, and Heng Ji. Meta-review generation with checklist-guided iterative introspection. arXiv preprint arXiv:2305.14647, 2023. — [arXiv:2305.14647](https://arxiv.org/abs/2305.14647) find
893. Qi Zeng, Mankeerat Sidhu, Ansel Blume, Hou Pong Chan, Lu Wang, and Heng Ji. Scientific opinion summarization: Paper meta-review generation dataset, methods, and evaluation. In Artificial Intelligence for Research and Democracy: First International Workshop, AI4Research 2024, and 4th International Wo… find
894. Yongchao Zeng, Calum Brown, Joanna Raymond, Mohamed Byari, Ronja Hotz, and Mark Rounsevell. Exploring the opportunities and challenges of using large language models to represent institutional agency in land system modelling. EGUsphere, 2024:1–35, Mar 2024. find
895. Chen Zhang, Yu Xie, Hang Bai, Bin Yu, Weihong Li, and Yuan Gao. A survey on federated learning. Knowledge-Based Systems, 216:106775, Mar 2021. find
896. Dan Zhang, Ziniu Hu, Sining Zhoubian, Zhengxiao Du, Kaiyu Yang, Zihan Wang, Yisong Yue, Yuxiao Dong, and Jie Tang. Sciglm: Training scientific language models with self-reflective instruction annotation and tuning. arXiv preprint arXiv:2401.07950, 2024. find
897. Daoze Zhang, Zhijian Bao, Sihang Du, Zhiyi Zhao, Kuangling Zhang, Dezheng Bao, and Yang Yang. Re 2 : A consistency-ensured dataset for full-stage peer review and multi-turn rebuttal discussions. arXiv preprint arXiv:2505.07920, 2025. — [arXiv:2505.07920](https://arxiv.org/abs/2505.07920) find
898. Fanjin Zhang, Shijie Shi, Yifan Zhu, Bo Chen, Yukuo Cen, Jifan Yu, Yelin Chen, Lulu Wang, Qingfei Zhao, Yuqing Cheng, Tianyi Han, Yuwei An, Dan Zhang, Weng Lam Tam, Kun Cao, Yunhe Pang, Xinyu Guan, Huihui Yuan, Jian Song, Xiaoyan Li, Yuxiao Dong, and Jie Tang. Oag-bench: A human-curated benchmark fo… — [arXiv:2402.15810](https://arxiv.org/abs/2402.15810) find
899. Guozhen Zhang, Zihan Yu, Nian Li, Fudan Yu, Qingyue Long, Depeng Jin, and Yong Li. Human behavior simulation: Objectives, methodologies, and open problems. arXiv preprint arXiv:2412.07788, 2024. — [arXiv:2412.07788](https://arxiv.org/abs/2412.07788) find
900. Jintian Zhang, Xin Xu, Ningyu Zhang, Ruibo Liu, Bryan Hooi, and Shumin Deng. Exploring collaboration mechanisms for llm agents: A social psychology view. arXiv preprint arXiv:2310.02124, 2023.
901. Lei Zhang, Yuge Zhang, Kan Ren, Dongsheng Li, and Yuqing Yang. Mlcopilot: Unleashing the power of large language models in solving machine learning tasks. arXiv preprint arXiv:2304.14979, 2023.
902. Leixin Zhang, Steffen Eger, Yinjie Cheng, Weihe Zhai, Jonas Belouadi, Christoph Leiter, Simone Paolo Ponzetto, Fahimeh Moafian, and Zhixue Zhao. Scimage: How good are multimodal large language models at scientific text-to-image generation? arXiv preprint arXiv:2412.02368, 2024. — [arXiv:2412.02368](https://arxiv.org/abs/2412.02368) find
903. Michael JQ Zhang and Eunsol Choi. Clarify when necessary: Resolving ambiguity through interaction with lms. arXiv preprint arXiv:2311.09469, 2023. find
904. Ming Zhang, Yujiong Shen, Zelin Li, Huayu Sha, Binze Hu, Yuhui Wang, Chenhao Huang, Shichun Liu, Jingqi Tong, Changhao Jiang, et al. Llmeval-med: A real-world clinical benchmark for medical llms with physician validation. arXiv preprint arXiv:2506.04078, 2025. find
905. Shujian Zhang, Chengyue Gong, Lemeng Wu, Xingchao Liu, and Mingyuan Zhou. Automl-gpt: Automatic machine learning with gpt. arXiv preprint arXiv:2305.02499, 2023.
906. Tao Zhang, Zhenhai Liu, Yong Xin, and Yongjun Jiao. Mooseagent: A llm based multi-agent framework for automating moose simulation. arXiv preprint arXiv:2504.08621, 2025. — [arXiv:2504.08621](https://arxiv.org/abs/2504.08621) find
907. Tianmai M Zhang and Neil F Abernethy. Reviewing scientific papers for critical problems with reasoning llms: Baseline approaches and automatic evaluation. arXiv preprint arXiv:2505.23824, 2025.
908. Xiaocheng Zhang, Xi Wang, Yifei Lu, Zhuangzhuang Ye, Jianing Wang, Mengjiao Bao, Peng Yan, and Xiaohong Su. Augmenting the veracity and explanations of complex fact checking via iterative self-revision with llms. arXiv preprint arXiv:2410.15135, 2024. — [arXiv:2410.15135](https://arxiv.org/abs/2410.15135) find
909. Xingjian Zhang, Yutong Xie, Jin Huang, Jinge Ma, Zhaoying Pan, Qijia Liu, Ziyang Xiong, Tolga Ergen, Dongsub Shim, Honglak Lee, et al. Massw: A new dataset and benchmark tasks for ai-assisted scientific workflows. arXiv preprint arXiv:2406.06357, 2024. find
910. Xinyu Zhang, Zongming Ni, Billy Fanady, Feibei Chen, Zijian Chen, Zixuan Wang, Guofei Chen, Zhengda He, Yang Bai, and Haitao Zhao. Chatgpt-assisted rational design for iterative performance optimization of perovskite solar cells. Available at SSRN 5127472, Feb . find
911. Xuan Zhang and Wei Gao. Towards llm-based fact verification on news claims with a hierarchical step-by-step prompting method. arXiv preprint arXiv:2310.00305, 2023. find
912. Xuanliang Zhang, Dingzirui Wang, Longxu Dou, Qingfu Zhu, and Wanxiang Che. A survey of table reasoning with large language models. Frontiers of Computer Science, 19(9):199348, Jan 2025. find
913. Yanbo Zhang, Sumeer A Khan, Adnan Mahmud, Huck Yang, Alexander Lavin, Michael Levin, Jeremy Frey, Jared Dunnmon, James Evans, Alan Bundy, et al. Advancing the scientific method with large language models: From hypothesis to discovery. arXiv preprint arXiv:2505.16477, 2025. — [arXiv:2505.16477](https://arxiv.org/abs/2505.16477) find
914. Yang Zhang, Yufei Wang, Kai Wang, Quan Z Sheng, Lina Yao, Adnan Mahmood, Wei Emma Zhang, and Rongying Zhao. When large language models meet citation: A survey. arXiv preprint arXiv:2309.09727, 2023. — [arXiv:2309.09727](https://arxiv.org/abs/2309.09727) find
915. Yongheng Zhang, Qiguang Chen, Min Li, Wanxiang Che, and Libo Qin. Autocap: Towards automatic cross-lingual alignment planning for zero-shot chain-of-thought. arXiv preprint arXiv:2406.13940, 2024. find
916. Yongheng Zhang, Qiguang Chen, Jingxuan Zhou, Peng Wang, Jiasheng Si, Jin Wang, Wenpeng Lu, and Libo Qin. Wrong-of-thought: An integrated reasoning framework with multi-perspective verification and wrong information. arXiv preprint arXiv:2410.04463, 2024. find
917. Yongheng Zhang, Xu Liu, Ruoxi Zhou, Qiguang Chen, Hao Fei, Wenpeng Lu, and Libo Qin. Cchall: A novel benchmark for joint cross-lingual and cross-modal hallucinations detection in large language models. arXiv preprint arXiv:2505.19108, 2025. find
918. Yu Zhang, Xiusi Chen, Bowen Jin, Sheng Wang, Shuiwang Ji, Wei Wang, and Jiawei Han. A comprehensive survey of scientific large language models and their applications in scientific discovery. arXiv preprint arXiv:2406.10833, 2024. find
919. Yunxiang Zhang, Muhammad Khalifa, Shitanshu Bhushan, Grant D Murphy, Lajanugen Logeswaran, Jaekyeom Kim, Moontae Lee, Honglak Lee, and Lu Wang. Mlrc-bench: Can language agents solve machine learning research challenges? arXiv preprint arXiv:2504.09702, 2025. find
920. Yuyu Zhang, Jing Su, Yifan Sun, Chenguang Xi, Xia Xiao, Shen Zheng, Anxiang Zhang, Kaibo Liu, Daoguang Zan, Tao Sun, et al. Seed-coder: Let the code model curate data for itself. arXiv preprint arXiv:2506.03524, 2025.
921. Zhihan Zhang, Yixin Cao, and Lizi Liao. Enhancing chart-to-code generation in multimodal large language models via iterative dual preference learning. arXiv preprint arXiv:2504.02906, 2025. — [arXiv:2504.02906](https://arxiv.org/abs/2504.02906) find
922. Chenlong Zhao, Xiwen Zhou, Xiaopeng Xie, and Yong Zhang. Hierarchical attention graph for scientific document summarization in global and local level. arXiv preprint arXiv:2405.10202, 2024. find
923. Haiteng Zhao, Chang Ma, Fangzhi Xu, Lingpeng Kong, and Zhi-Hong Deng. Biomaze: Benchmarking and enhancing large language models for biological pathway reasoning. arXiv preprint arXiv:2502.16660, 2025. — [arXiv:2502.16660](https://arxiv.org/abs/2502.16660) find
924. Haiyan Zhao, Fan Yang, Bo Shen, Himabindu Lakkaraju, and Mengnan Du. Towards uncovering how large language model works: An explainability perspective. arXiv preprint arXiv:2402.10688, 2024. — [arXiv:2402.10688](https://arxiv.org/abs/2402.10688) find
925. Henry Hengyuan Zhao, Wenqi Pei, Yifei Tao, Haiyang Mei, and Mike Zheng Shou. Interfeedback: Unveiling interactive intelligence of large multimodal models via human feedback. arXiv preprint arXiv:2502.15027, 2025. — [arXiv:2502.15027](https://arxiv.org/abs/2502.15027) find
926. Penghai Zhao, Qinghua Xing, Kairan Dou, Jinyu Tian, Ying Tai, Jian Yang, Ming-Ming Cheng, and Xiang Li. From words to worth: Newborn article impact prediction with llm. In Proceedings of the AAAI Conference on Artificial Intelligence, volume 39, pages 1183–1191, Jan 2025. URL https://ojs.aaai.org/in… ↗
927. Wayne Xin Zhao, Kun Zhou, Junyi Li, Tianyi Tang, Xiaolei Wang, Yupeng Hou, Yingqian Min, Beichen Zhang, Junjie Zhang, Zican Dong, et al. A survey of large language models. arXiv preprint arXiv:2303.18223, 1(2), 2023.
928. Xuanle Zhao, Xianzhen Luo, Qi Shi, Chi Chen, Shuo Wang, Zhiyuan Liu, and Maosong Sun. Chartcoder: Advancing multimodal large language model for chart-to-code generation. arXiv preprint arXiv:2501.06598, 2025.
929. Xuanle Zhao, Zilin Sang, Yuxuan Li, Qi Shi, Shuo Wang, Duzhen Zhang, Xu Han, Zhiyuan Liu, and Maosong Sun. Autoreproduce: Automatic ai experiment reproduction with paper lineage. arXiv preprint arXiv:2505.20662, 2025. find
930. Xueliang Zhao, Wenda Li, and Lingpeng Kong. Decomposing the enigma: Subgoal-based demonstration learning for formal theorem proving. arXiv preprint arXiv:2305.16366, 2023. find
931. Yilun Zhao, Chengye Wang, Chuhan Li, and Arman Cohan. Can multimodal foundation models understand schematic diagrams? an empirical study on information-seeking QA over scientific papers. In Findings of the Association for Computational Linguistics: ACL 2025, pages 18598–18631, 2025. find
932. Yilun Zhao, Kaiyan Zhang, Tiansheng Hu, Sihong Wu, Ronan Le Bras, Taira Anderson, Jonathan Bragg, Joseph Chee Chang, Jesse Dodge, Matt Latzke, et al. Sciarena: An open evaluation platform for foundation models in scientific literature tasks. arXiv preprint arXiv:2507.01001, 2025.
933. Yiming Zhao, Yongjia Zhao, Jian Wang, and Zhuo Wang. Artificial intelligence meets laboratory automation in discovery and synthesis of metal–organic frameworks: A review. Industrial & Engineering Chemistry Research, 64(9):4637–4668, Feb 2025. find
934. Bo Zheng, Zhouyang Li, Fuxuan Wei, Qiguang Chen, Libo Qin, and Wanxiang Che. Hit-scir at mmnlu-22: Consistency regularization for multilingual spoken language understanding. arXiv preprint arXiv:2301.02010, 2023. find
935. Kunhao Zheng, Jesse Michael Han, and Stanislas Polu. Minif2f: a cross-system benchmark for formal olympiad-level mathematics. arXiv preprint arXiv:2109.00110, 2021.
936. Mingyu Zheng, Xinwei Feng, Qingyi Si, Qiaoqiao She, Zheng Lin, Wenbin Jiang, and Weiping Wang. Multimodal table understanding. In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 9102–9124, Jun 2024.
937. Ruiqi Zheng, Liang Qu, Bin Cui, Yuhui Shi, and Hongzhi Yin. Automl for deep recommender systems: A survey. ACM Trans. Inf. Syst., 41(4), March 2023. ISSN 1046-8188. doi: 10.1145/3579355. URL https://doi.org/10.1145/3579355. — [doi:10.1145/3579355](https://doi.org/10.1145/3579355) ↗
938. Shenghe Zheng, Qianjia Cheng, Junchi Yao, Mengsong Wu, Ning Ding, Yu Cheng, Shuyue Hu, Lei Bai, Dongzhan Zhou, Ganqu Cui, et al. Scaling physical reasoning with the physics dataset. arXiv preprint arXiv:2506.00022, 2025. — [arXiv:2506.00022](https://arxiv.org/abs/2506.00022) find
939. Tianshi Zheng, Zheye Deng, Hong Ting Tsang, Weiqi Wang, Jiaxin Bai, Zihao Wang, and Yangqiu Song. From automation to autonomy: A survey on large language models in scientific discovery. arXiv preprint arXiv:2505.13259, 2025. find
940. Xiaofeng Zheng and Jian Zhang. The usage of a transformer based and artificial intelligence driven multidimensional feedback system in english writing instruction. Scientific Reports, 15(1):1–22, Jun 2025. find
941. Tianyang Zhong, Zhengliang Liu, Yi Pan, Yutong Zhang, Yifan Zhou, Shizhe Liang, Zihao Wu, Yanjun Lyu, Peng Shu, Xiaowei Yu, et al. Evaluation of openai o1: Opportunities and challenges of agi. arXiv preprint arXiv:2409.18486, 2024.
942. Junting Zhou, Wang Li, Yiyan Liao, Nengyuan Zhang, Tingjia Miaoand Zhihui Qi, Yuhan Wu, and Tong Yang. Academicbrowse: Benchmarking academic browse ability of llms. arXiv preprint arXiv:2506.13784, 2025. — [arXiv:2506.13784](https://arxiv.org/abs/2506.13784) find
943. Li Zhou, Ruijie Zhang, Xunlian Dai, Daniel Hershcovich, and Haizhou Li. Large language models penetration in scholarly writing and peer review. arXiv preprint arXiv:2502.11193, 2025. — [arXiv:2502.11193](https://arxiv.org/abs/2502.11193) find
944. Ruiyang Zhou, Lu Chen, and Kai Yu. Is llm a reliable reviewer? a comprehensive evaluation of llm on automatic paper reviewing tasks. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 9340–9351, May 2024…
945. Yangqiaoyu Zhou, Haokun Liu, Tejes Srivastava, Hongyuan Mei, and Chenhao Tan. Hypothesis generation with large language models. arXiv preprint arXiv:2404.04326, 2024. find
946. Yilun Zhou, Caiming Xiong, Silvio Savarese, and Chien-Sheng Wu. Shared imagination: Llms hallucinate alike. arXiv preprint arXiv:2407.16604, 2024.
947. Haonan Zhu, Mary Silva, Jose Cadena, Braden Soper, Michał Lisicki, Braian Peetoom, Sergio E Baranzini, Shivshankar Sundaram, Priyadip Ray, and Jeff Drocco. Deep active learning based experimental design to uncover synergistic genetic interactions for host targeted therapeutics. arXiv preprint arXiv:… — [arXiv:2502.01012](https://arxiv.org/abs/2502.01012) find
948. Kun Zhu, Xiaocheng Feng, Xiachong Feng, Yingsheng Wu, and Bing Qin. Hierarchical catalogue generation for literature review: a benchmark. arXiv preprint arXiv:2304.03512, 2023. find
949. Kunlun Zhu, Jiaxun Zhang, Ziheng Qi, Nuoxing Shang, Zijia Liu, Peixuan Han, Yue Su, Haofei Yu, and Jiaxuan You. Safescientist: Toward risk-aware scientific discoveries by llm agents. arXiv preprint arXiv:2505.23559, 2025. find
950. Minjun Zhu, Yixuan Weng, Linyi Yang, and Yue Zhang. Deepreview: Improving llm-based paper review with human-like deep thinking process. arXiv preprint arXiv:2503.08569, 2025. find
951. Minjun Zhu, Qiujie Xie, Yixuan Weng, Jian Wu, Zhen Lin, Linyi Yang, and Yue Zhang. Ai scientists fail without strong implementation capability. arXiv preprint arXiv:2506.01372, 2025. find
952. Qing Zhu, Yan Huang, Donglai Zhou, Luyuan Zhao, Lulu Guo, Ruyu Yang, Zixu Sun, Man Luo, Fei Zhang, Hengyu Xiao, et al. Automated synthesis of oxygen-producing catalysts from martian meteorites by a robotic ai chemist. Nature Synthesis, 3(3):319–328, 2024. find
953. Ronghang Zhu, Dongliang Guo, Daiqing Qi, Zhixuan Chu, Xiang Yu, and Sheng Li. A survey of trustworthy representation learning across domains. ACM Transactions on Knowledge Discovery from Data, 18(7):1–53, Jun 2024. find
954. Xiaodan Zhu, Peter Turney, Daniel Lemire, and André Vellino. Measuring academic influence: Not all citations are equal. Journal of the Association for Information Science and Technology, 66(2):408–427, Jan 2015. find
955. Jun Zhuang and Casey Kennington. Understanding survey paper taxonomy about large language models via graph representation learning. In Tirthankar Ghosal, Amanpreet Singh, Anita Waard, Philipp Mayr, Aakanksha Naik, Orion Weller, Yoonjoo Lee, Shannon Shen, and Yanxia Qin, editors, Proceedings of the F… find
956. Zhenzhen Zhuang, Jiandong Chen, Hongfeng Xu, Yuwen Jiang, and Jialiang Lin. Large language models for automated scholarly paper review: A survey. arXiv preprint arXiv:2501.10326, 2025. — [arXiv:2501.10326](https://arxiv.org/abs/2501.10326) find
957. Ziyu Zhuang, Qiguang Chen, Longxuan Ma, Mingda Li, Yi Han, Yushan Qian, Haopeng Bai, Zixian Feng, Weinan Zhang, and Ting Liu. Through the lens of core competency: Survey on evaluation of large language models. arXiv preprint arXiv:2308.07902, 2023.
958. Yoel Zimmermann, Adib Bazgir, Alexander Al-Feghali, Mehrad Ansari, L Catherine Brinson, Yuan Chiang, Defne Circi, Min-Hsueh Chiu, Nathan Daelman, Matthew L Evans, et al. 34 examples of llm applications in materials science and chemistry: Towards automation, assistants, agents, and accelerated scient… — [arXiv:2505.03049](https://arxiv.org/abs/2505.03049) find
959. James Zou and Eric J Topol. The rise of agentic ai teammates in medicine. The Lancet, 405(10477): 457, Feb 2025. find
960. Apostolos Zournas, Matthew R Incha, Tijana Radivojevic, Vincent Blay, Jose Manuel Martí, Zak Costello, Matthias Schimdt, Tan Chung, Mitchell G Thompson, Allison Pearson, et al. Machine learning-led semi-automated medium optimization reveals salt as key for flaviolin production in pseudomonas putida.… find

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