🧑‍🔬 Who cites Ryan Liu

67 citations of their works from 67 papers of our library (of the 149,439 whose bibliographies we read) · 34 with a page here, the most cited first · ← Ryan Liu

1. A Survey of Large Language ModelsFrontiers of Computer ScienceWayne Xin Zhao, Kun Zhou, Junyi Li, et al.2023 · 2,875 citations
2. Can large language models provide useful feedback on research papers? A large-scale empirical analysisNEJM AIWeixin Liang, Yuhui Zhang, Hancheng Cao, et al.2023 · 332 citations
3. Challenges and Applications of Large Language ModelsarXiv:2307.10169Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.2023 · 301 citations
4. Monitoring AI-Modified Content at Scale: A Case Study on the Impact of ChatGPT on AI Conference Peer ReviewsarXiv:2403.07183Weixin Liang, Zachary Izzo, Yaohui Zhang, et al.2024 · 119 citations
5. Mapping the Increasing Use of LLMs in Scientific PapersarXiv:2404.01268Weixin Liang, Yaohui Zhang, Zhengxuan Wu, et al.2024 · 89 citations
6. MARG: Multi-Agent Review Generation for Scientific PapersarXiv:2401.04259Mike D'Arcy, Tom Hope, Larry Birnbaum, et al.2024 · 76 citations
7. Is LLM a Reliable Reviewer? A Comprehensive Evaluation of LLM on Automatic Paper Reviewing TasksLanguage Resources and Evaluation Conference (LREC)Ruiyang Zhou, Lu Chen, Kai Yu2024 · 74 citations
8. LLMs Assist NLP Researchers: Critique Paper (Meta-)ReviewingConference on Empirical Methods in Natural Language Processing (EMNLP)Jiangshu Du, Yibo Wang, Wenting Zhao, et al.2024 · 71 citations
9. CycleResearcher: Improving Automated Research via Automated ReviewarXiv:2411.00816Yixuan Weng, Minjun Zhu, Guangsheng Bao, et al.2024 · 65 citations
10. From Automation to Autonomy: A Survey on Large Language Models in Scientific DiscoveryConference on Empirical Methods in Natural Language Processing (EMNLP)Tianshi Zheng, Zheye Deng, Hong Ting Tsang, et al.2025 · 39 citations
11. LLM4SR: A Survey on Large Language Models for Scientific ResearcharXiv:2501.04306Ziming Luo, Zonglin Yang, Zexin Xu, et al.2025 · 39 citations
12. Are We There Yet? Revealing the Risks of Utilizing Large Language Models in Scholarly Peer ReviewarXiv:2412.01708Rui Ye, Xianghe Pang, Jingyi Chai, et al.2024 · 35 citations
13. AI-Driven Review Systems: Evaluating LLMs in Scalable and Bias-Aware Academic ReviewsarXiv:2408.10365Keith Tyser, Ben Segev, Gaston Longhitano, et al.2024 · 34 citations
14. What Can Natural Language Processing Do for Peer Review?arXiv:2405.06563Ilia Kuznetsov, Osama Mohammed Afzal, Koen Dercksen, et al.2024 · 33 citations
15. Peer Reviews of Peer Reviews: A Randomized Controlled Trial and Other ExperimentsPLoS ONEAlexander Goldberg, Ivan Stelmakh, Kyunghyun Cho, et al.2023 · 32 citations
16. Reviewer2: Optimizing Review Generation Through Prompt GenerationarXiv:2402.10886Zhaolin Gao, Kiante Brantley, Thorsten Joachims2024 · 27 citations
17. Transforming Science with Large Language Models: A Survey on AI-assisted Scientific Discovery, Experimentation, Content Generation, and EvaluationACM Computing SurveysSteffen Eger, Yong Cao, Jennifer D'Souza, et al.2025 · 25 citations
18. AI4Research: A Survey of Artificial Intelligence for Scientific ResearchScience China Information SciencesQiguang Chen, Mingda Yang, Libo Qin, et al.2025 · 21 citations
19. Can LLM feedback enhance review quality? A randomized study of 20K reviews at ICLR 2025arXiv:2504.09737Nitya Thakkar, Mert Yuksekgonul, Jake Silberg, et al.2025 · 21 citations
20. MLR-Bench: Evaluating AI Agents on Open-Ended Machine Learning ResearchConference on Neural Information Processing Systems (NeurIPS)Hui Chen, Miao Xiong, Yujie Lu, et al.2025 · 21 citations
21. Position: The AI Conference Peer Review Crisis Demands Author Feedback and Reviewer RewardsarXiv:2505.04966Jaeho Kim, Yunseok Lee, Seulki Lee2025 · 13 citations
22. Can LLMs Identify Critical Limitations within Scientific Research? A Systematic Evaluation on AI Research PapersAnnual Meeting of the Association for Computational Linguistics (ACL)Zhijian Xu, Yilun Zhao, Manasi Patwardhan, et al.2025 · 11 citations
23. The More You Automate, the Less You See: Hidden Pitfalls of AI Scientist SystemsarXiv:2509.08713Ziming Luo, Atoosa Kasirzadeh, Nihar B. Shah2025 · 11 citations
24. Reproducibility in Machine Learning-Driven ResearcharXiv:2307.10320Harald Semmelrock, Simone Kopeinik, Dieter Theiler, et al.2023 · 11 citations
25. Usefulness of LLMs as an Author Checklist Assistant for Scientific Papers: NeurIPS'24 ExperimentarXiv:2411.03417Alexander Goldberg, Ihsan Ullah, Thanh Gia Hieu Khuong, et al.2024 · 10 citations
26. REMOR: Automated Peer Review Generation with LLM Reasoning and Multi-Objective Reinforcement LearningarXiv:2505.11718Pawin Taechoyotin, Daniel Acuna2025 · 8 citations
27. Reviewing Scientific Papers for Critical Problems With Reasoning LLMs: Baseline Approaches and Automatic EvaluationarXiv:2505.23824Tianmai M. Zhang, Neil F. Abernethy2025 · 7 citations
28. Automatic Reviewers Fail to Detect Faulty Reasoning in Research Papers: A New Counterfactual Evaluation FrameworkTransactions of the Association for Computational Linguistics (TACL)Nils Dycke, Iryna Gurevych2026 · 5 citations
29. Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box SystemsarXiv:2505.17968Jiayi Geng, Howard Chen, Dilip Arumugam, et al.2025 · 4 citations
30. RbtAct: Rebuttal as Supervision for Actionable Review Feedback GenerationFindings of the Association for Computational LinguisticsSihong Wu, Yiling Ma, Yilun Zhao, et al.2026 · 2 citations
31. "Give a Positive Review Only": An Early Investigation Into In-Paper Prompt Injection Attacks and Defenses for AI ReviewersarXiv:2511.01287Qin Zhou, Zhexin Zhang, Zhi Li, et al.2025 · 2 citations
32. Can AI Be a Good Peer Reviewer? A Survey of Peer Review Process, Evaluation, and the FutureAnnual Meeting of the Association for Computational Linguistics (ACL)Sihong Wu, Owen Jiang, Yilun Zhao, et al.2026 · 1 citation
33. PaperMentor: A Human-Centered Multi-Agent Writing Tutor for AI Research Papers in OverleafAnnual Meeting of the Association for Computational Linguistics (ACL)Jiarui Liu, Terry Jingchen Zhang, Ryan Faulkner, et al.2026 · 1 citation
34. From Isolated Scoring to Collaborative Ranking: A Comparison-Native Framework for LLM-Based Paper EvaluationFindings of the Association for Computational LinguisticsPujun Zheng, Jiacheng Yao, Jinquan Zheng, et al.2026

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