🧑‍🔬 Who cites Nitya Nadgir

94 citations of their works from 85 papers of our library (of the 149,439 whose bibliographies we read) · 32 with a page here, the most cited first · ← Nitya Nadgir

1. MLE-bench: Evaluating Machine Learning Agents on Machine Learning EngineeringarXiv:2410.07095Jun Shern Chan, Neil Chowdhury, Oliver Jaffe, et al.2024 · 140 citations
2. Why Do Multi-Agent LLM Systems Fail?arXiv:2503.13657Mert Cemri, Melissa Z. Pan, Shuyi Yang, et al.2025 · 89 citations
3. PaperBench: Evaluating AI's Ability to Replicate AI ResearcharXiv:2504.01848Giulio Starace, Oliver Jaffe, Dane Sherburn, et al.2025 · 86 citations
4. More Agents Is All You NeedarXiv:2402.05120Junyou Li, Qin Zhang, Yangbin Yu, et al.2024 · 85 citations
5. ScienceAgentBench: Toward Rigorous Assessment of Language Agents for Data-Driven Scientific DiscoveryarXiv:2410.05080Ziru Chen, Shijie Chen, Yuting Ning, et al.2024 · 81 citations
6. Magentic-One: A Generalist Multi-Agent System for Solving Complex TasksarXiv:2411.04468Adam Fourney, Gagan Bansal, Hussein Mozannar, et al.2024 · 54 citations
7. RLEF: Grounding Code LLMs in Execution Feedback with Reinforcement LearningarXiv:2410.02089Jonas Gehring, Kunhao Zheng, Jade Copet, et al.2024 · 51 citations
8. MLGym: A New Framework and Benchmark for Advancing AI Research AgentsarXiv:2502.14499Deepak Nathani, Lovish Madaan, Nicholas Roberts, et al.2025 · 50 citations
9. A Survey of Frontiers in LLM Reasoning: Inference Scaling, Learning to Reason, and Agentic SystemsarXiv:2504.09037Zixuan Ke, Fangkai Jiao, Yifei Ming, et al.2025 · 39 citations
10. LLM4SR: A Survey on Large Language Models for Scientific ResearcharXiv:2501.04306Ziming Luo, Zonglin Yang, Zexin Xu, et al.2025 · 39 citations
11. CORE-Bench: Fostering the Credibility of Published Research Through a Computational Reproducibility Agent BenchmarkarXiv:2409.11363Zachary S. Siegel, Sayash Kapoor, Nitya Nadgir, et al.2024 · 39 citations
12. Towards Scientific Intelligence: A Survey of LLM-based Scientific AgentsarXiv:2503.24047Shuo Ren, Can Xie, Pu Jian, et al.2025 · 24 citations
13. SciReplicate-Bench: Benchmarking LLMs in Agent-driven Algorithmic Reproduction from Research PapersarXiv:2504.00255Yanzheng Xiang, Hanqi Yan, Shuyin Ouyang, et al.2025 · 23 citations
14. A Survey on Evaluation of LLM-based AgentsFindings of the Association for Computational LinguisticsAsaf Yehudai, Lilach Eden, Alan Li, et al.2026 · 21 citations
15. The Limits of Inference Scaling Through ResamplingarXiv:2411.17501Benedikt Stroebl, Sayash Kapoor, Arvind Narayanan2024 · 21 citations
16. AstaBench: Rigorous Benchmarking of AI Agents with a Scientific Research SuitearXiv:2510.21652Jonathan Bragg, Mike D'Arcy, Nishant Balepur, et al.2025 · 19 citations
17. ResearchCodeBench: Benchmarking LLMs on Implementing Novel Machine Learning Research CodeConference on Neural Information Processing Systems (NeurIPS)Tianyu Hua; Harper Hua; Violet Xiang; Benjamin Klieger; Sang T. Truong; Weixin Liang; Fan-Yun Sun;, Nick Haber2025 · 16 citations
18. MLRC-Bench: Can Language Agents Solve Machine Learning Research Challenges?Conference on Neural Information Processing Systems (NeurIPS)Yunxiang Zhang, Muhammad Khalifa, Shitanshu Bhushan, et al.2025 · 13 citations
19. When AI Co-Scientists Fail: SPOT-a Benchmark for Automated Verification of Scientific ResearcharXiv:2505.11855Guijin Son, Jiwoo Hong, Honglu Fan, et al.2025 · 13 citations
20. AI Scientists Fail Without Strong Implementation CapabilityarXiv:2506.01372Minjun Zhu, Qiujie Xie, Yixuan Weng, et al.2025 · 12 citations
21. AutoReproduce: Automatic AI Experiment Reproduction with Paper LineageAnnual Meeting of the Association for Computational Linguistics (ACL)Xuanle Zhao, Zilin Sang, Yuxuan Li, et al.2025 · 12 citations
22. TRAIL: Trace Reasoning and Agentic Issue LocalizationarXiv:2505.08638Darshan Deshpande, Varun Gangal, Hersh Mehta, et al.2025 · 12 citations
23. Holistic Agent Leaderboard: The Missing Infrastructure for AI Agent EvaluationarXiv:2510.11977Sayash Kapoor, Benedikt Stroebl, Peter Kirgis, et al.2025 · 11 citations
24. Localized Cultural Knowledge is Conserved and Controllable in Large Language ModelsFindings of the Association for Computational LinguisticsVeniamin Veselovsky, Berke Argın, Benedikt Stroebl, et al.2026 · 7 citations
25. How Far Are We From True Auto-Research?arXiv:2605.19156Zhengxin Zhang, Ning Wang, Sainyam Galhotra, et al.2026 · 5 citations
26. Uncertainty Quantification in LLM Agents: Foundations, Emerging Challenges, and OpportunitiesAnnual Meeting of the Association for Computational Linguistics (ACL)Changdae Oh, Seongheon Park, To Eun Kim, et al.2026 · 4 citations
27. Debate Only When Necessary: Adaptive Multiagent Collaboration for Efficient LLM ReasoningarXiv:2504.05047Sugyeong Eo, Hyeonseok Moon, Evelyn Hayoon Zi, et al.2025 · 4 citations
28. The Automated LLM Speedrunning Benchmark: Reproducing NanoGPT ImprovementsConference on Neural Information Processing Systems (NeurIPS)Bingchen Zhao, Despoina Magka, Minqi Jiang, et al.2025 · 4 citations
29. Training AI Scientists to Replicate ResearcharXiv:2608.13331Damon Falck, Samer Sabri, Anja Surina, et al.2026 · 2 citations
30. Agentic CLEAR: Automating Multi-Level Evaluation of LLM AgentsAnnual Meeting of the Association for Computational Linguistics (ACL)Asaf Yehudai, Lilach Eden, Michal Shmueli-Scheuer2026
31. Efficient Agent Evaluation via Diversity-Guided User SimulationAnnual Meeting of the Association for Computational Linguistics (ACL)Itay Nakash, George Kour, Ateret Anaby Tavor2026
32. What Moves the Pareto Frontier in Tool-Using Agents? A Compute-Aware Study of ReAct VariantsAnnual Meeting of the Association for Computational Linguistics (ACL)Rishi N. Simhadri2026

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