🧑‍🔬 Who cites Larry Birnbaum

79 citations of their works from 79 papers of our library (of the 149,439 whose bibliographies we read) · 44 with a page here, the most cited first · ← Larry Birnbaum

1. oLMpics — On what Language Model Pre-training CapturesTransactions of the Association for Computational Linguistics (TACL)Alon Talmor, Yanai Elazar, Yoav Goldberg, et al.2019 · 440 citations
2. The AI Scientist: Towards Fully Automated Open-Ended Scientific DiscoveryarXiv:2408.06292Chris Lu, Cong Lu, Robert Tjarko Lange, et al.2024 · 372 citations
3. Do NLP Models Know Numbers? Probing Numeracy in EmbeddingsConference on Empirical Methods in Natural Language Processing (EMNLP)Eric Wallace, Yizhong Wang, Sujian Li, et al.2019 · 352 citations
4. Generative Data Augmentation for Commonsense ReasoningFindings of the Association for Computational LinguisticsYiben Yang, Chaitanya Malaviya, Jared Fernandez, et al.2020 · 198 citations
5. Can LLMs Generate Novel Research Ideas? A Large-Scale Human Study with 100+ NLP ResearchersarXiv:2409.04109Chenglei Si, Diyi Yang, Tatsunori Hashimoto2024 · 196 citations
6. Agent Laboratory: Using LLM Agents as Research AssistantsarXiv:2501.04227Samuel Schmidgall, Yusheng Su, Ze Wang, et al.2025 · 139 citations
7. Recent Advances in Natural Language Inference: A Survey of Benchmarks, Resources, and ApproachesarXiv:1904.01172Shane Storks, Qiaozi Gao, Joyce Y. Chai2019 · 135 citations
8. Multi-Agent Collaboration Mechanisms: A Survey of LLMsarXiv:2501.06322Khanh-Tung Tran, Dung Dao, Minh-Duong Nguyen, et al.2025 · 95 citations
9. AgentReview: Exploring Peer Review Dynamics with LLM AgentsConference on Empirical Methods in Natural Language Processing (EMNLP)Yiqiao Jin, Qinlin Zhao, Yiyang Wang, et al.2024 · 86 citations
10. Do Language Embeddings capture Scales?Findings of the Association for Computational LinguisticsXikun Zhang, Deepak Ramachandran, Ian Tenney, et al.2020 · 75 citations
11. CycleResearcher: Improving Automated Research via Automated ReviewarXiv:2411.00816Yixuan Weng, Minjun Zhu, Guangsheng Bao, et al.2024 · 65 citations
12. Magentic-One: A Generalist Multi-Agent System for Solving Complex TasksarXiv:2411.04468Adam Fourney, Gagan Bansal, Hussein Mozannar, et al.2024 · 54 citations
13. DeepReview: Improving LLM-based Paper Review with Human-like Deep Thinking ProcessAnnual Meeting of the Association for Computational Linguistics (ACL)Minjun Zhu, Yixuan Weng, Linyi Yang, et al.2025 · 52 citations
14. AgentRxiv: Towards Collaborative Autonomous ResearcharXiv:2503.18102Samuel Schmidgall, Michael Moor2025 · 39 citations
15. LLM4SR: A Survey on Large Language Models for Scientific ResearcharXiv:2501.04306Ziming Luo, Zonglin Yang, Zexin Xu, et al.2025 · 39 citations
16. 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
17. What Can Natural Language Processing Do for Peer Review?arXiv:2405.06563Ilia Kuznetsov, Osama Mohammed Afzal, Koen Dercksen, et al.2024 · 33 citations
18. ARIES: A Corpus of Scientific Paper Edits Made in Response to Peer ReviewsAnnual Meeting of the Association for Computational Linguistics (ACL)Mike D'Arcy, Alexis Ross, Erin Bransom, et al.2024 · 32 citations
19. Peer Reviews of Peer Reviews: A Randomized Controlled Trial and Other ExperimentsPLoS ONEAlexander Goldberg, Ivan Stelmakh, Kyunghyun Cho, et al.2023 · 32 citations
20. 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
21. Paper2Code: Automating Code Generation from Scientific Papers in Machine LearningarXiv:2504.17192Minju Seo, Jinheon Baek, Seongyun Lee, et al.2025 · 24 citations
22. AI4Research: A Survey of Artificial Intelligence for Scientific ResearchScience China Information SciencesQiguang Chen, Mingda Yang, Libo Qin, et al.2025 · 21 citations
23. 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
24. 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
25. Automated Hypothesis Validation with Agentic Sequential FalsificationsarXiv:2502.09858Kexin Huang, Ying Jin, Ryan Li, et al.2025 · 19 citations
26. From AI for Science to Agentic Science: A Survey on Autonomous Scientific DiscoveryarXiv:2508.14111Jiaqi Wei, Yuejin Yang, Xiang Zhang, et al.2025 · 19 citations
27. TreeReview: A Dynamic Tree of Questions Framework for Deep and Efficient LLM-based Scientific Peer ReviewConference on Empirical Methods in Natural Language Processing (EMNLP)Yuan Chang, Ziyue Li, Hengyuan Zhang, et al.2025 · 16 citations
28. Mind the Blind Spots: A Focus-Level Evaluation Framework for LLM ReviewsConference on Empirical Methods in Natural Language Processing (EMNLP)Hyungyu Shin, Jingyu Tang, Yoonjoo Lee, et al.2025 · 14 citations
29. How Pre-trained Word Representations Capture Commonsense Physical ComparisonsWorkshop on Commonsense Inference in Natural Language ProcessingPranav Goel, Shi Feng, Jordan Boyd-Graber2019 · 12 citations
30. 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
31. The More You Automate, the Less You See: Hidden Pitfalls of AI Scientist SystemsarXiv:2509.08713Ziming Luo, Atoosa Kasirzadeh, Nihar B. Shah2025 · 11 citations
32. 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
33. AbGen: Evaluating Large Language Models in Ablation Study Design and Evaluation for Scientific ResearchAnnual Meeting of the Association for Computational Linguistics (ACL)Yilun Zhao, Weiyuan Chen, Zhijian Xu, et al.2025 · 9 citations
34. REMOR: Automated Peer Review Generation with LLM Reasoning and Multi-Objective Reinforcement LearningarXiv:2505.11718Pawin Taechoyotin, Daniel Acuna2025 · 8 citations
35. Reviewing Scientific Papers for Critical Problems With Reasoning LLMs: Baseline Approaches and Automatic EvaluationarXiv:2505.23824Tianmai M. Zhang, Neil F. Abernethy2025 · 7 citations
36. AI for Auto-Research: Roadmap & User GuidearXiv:2605.18661Lingdong Kong, Xian Sun, Wei Chow, et al.2026 · 5 citations
37. 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
38. Paper2Rebuttal: A Multi-Agent Framework for Transparent Author Response AssistanceAnnual Meeting of the Association for Computational Linguistics (ACL)Qianli Ma, Chang Guo, Zhiheng Tian, et al.2026 · 5 citations
39. NovBench: Evaluating Large Language Models on Academic Paper Novelty AssessmentFindings of the Association for Computational LinguisticsWenqing Wu, Yi Zhao, Yuzhuo Wang, et al.2026 · 4 citations
40. 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
41. 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
42. 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
43. ARAMIS: a web tool integrated with an open-source LLM to support grading undergraduate theses (ARAMIS: Uma ferramenta web integrada com LLM open-source para apoio à correção de TCCs de estudantes de graduação)International Conference on Computational Processing of PortugueseGustavo Campelo de Sousa, Pablo Kauan Martins Timbó, Luiz Zairo Bastos Viana, et al.2026
44. Preference Optimization for Review Question Generation Improves Writing QualityFindings of the Association for Computational LinguisticsKarun Sharma, Vidushee Vats, Shengzhi LI, et al.2026

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