---
title: "Who cites Sayash Kapoor — 222 papers of our library"
description: "222 papers of the Elamur Research library cite the works of Sayash Kapoor, found in their bibliographies; the most cited first."
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---
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# Who cites Sayash Kapoor

291 citations of their works from 222 papers of our library (of the 149,439 whose bibliographies we read) · 66 with a page here, the most cited first · [← Sayash Kapoor](https://md.research.elamur.ai/free/en/authors/sayash-kapoor/)

1. **[JailbreakBench: An Open Robustness Benchmark for Jailbreaking Large Language Models](https://md.research.elamur.ai/free/en/papers/chao-2024-jailbreakbench-open-robustness-benchmark-jailbreaking/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Patrick Chao, Edoardo Debenedetti, Alexander Robey, et al.*2024 · 277 citations*
2. [**Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools arXiv:2405.20362**Varun Magesh, Faiz Surani, Matthew Dahl, et al.*2024 · 271 citations*](https://md.research.elamur.ai/free/en/papers/magesh-2024-hallucination-free-assessing-reliability-leading/)
3. **[RedPajama: an Open Dataset for Training Large Language Models](https://md.research.elamur.ai/free/en/papers/weber-2024-redpajama-open-dataset-training-large/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Maurice Weber, Daniel Fu, Quentin Anthony, et al.*2024 · 260 citations*
4. [**TrustLLM: Trustworthiness in Large Language Models arXiv:2401.05561**Yue Huang, Lichao Sun, Haoran Wang, et al.*2024 · 237 citations*](https://md.research.elamur.ai/free/en/papers/huang-2024-trustllm-trustworthiness-large-language-models/)
5. **[Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2025-towards-reasoning-era-survey-long/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Libo Qin, Jinhao Liu, et al.*2025 · 176 citations*
6. [**SmoothLLM: Defending Large Language Models Against Jailbreaking Attacks arXiv:2310.03684**Alexander Robey, Eric Wong, Hamed Hassani, et al.*2023 · 164 citations*](https://md.research.elamur.ai/free/en/papers/robey-2023-smoothllm-defending-large-language-models/)
7. [**MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering arXiv:2410.07095**Jun Shern Chan, Neil Chowdhury, Oliver Jaffe, et al.*2024 · 140 citations*](https://md.research.elamur.ai/free/en/papers/chan-2024-mle-bench-evaluating-machine/)
8. [**A Survey on Data Selection for Language Models arXiv:2402.16827**Alon Albalak, Yanai Elazar, Sang Michael Xie, et al.*2024 · 95 citations*](https://md.research.elamur.ai/free/en/papers/albalak-2024-survey-data-selection-language-models/)
9. **[WildTeaming at Scale: From In-the-Wild Jailbreaks to (Adversarially) Safer Language Models](https://md.research.elamur.ai/free/en/papers/jiang-2024-wildteaming-scale-wild-jailbreaks-adversarially/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Liwei Jiang, Kavel Rao, Seungju Han, et al.*2024 · 92 citations*
10. [**Why Do Multi-Agent LLM Systems Fail? arXiv:2503.13657**Mert Cemri, Melissa Z. Pan, Shuyi Yang, et al.*2025 · 89 citations*](https://md.research.elamur.ai/free/en/papers/cemri-2025-why-multi-agent-llm/)
11. [**Foundational Challenges in Assuring Alignment and Safety of Large Language Models arXiv:2404.09932**Usman Anwar, Abulhair Saparov, Javier Rando, et al.*2024 · 87 citations*](https://md.research.elamur.ai/free/en/papers/anwar-2024-foundational-challenges-assuring-alignment-safety/)
12. [**PaperBench: Evaluating AI's Ability to Replicate AI Research arXiv:2504.01848**Giulio Starace, Oliver Jaffe, Dane Sherburn, et al.*2025 · 86 citations*](https://md.research.elamur.ai/free/en/papers/starace-2025-paperbench-evaluating-ai-s/)
13. [**More Agents Is All You Need arXiv:2402.05120**Junyou Li, Qin Zhang, Yangbin Yu, et al.*2024 · 85 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-more-agents-all-need/)
14. [**ScienceAgentBench: Toward Rigorous Assessment of Language Agents for Data-Driven Scientific Discovery arXiv:2410.05080**Ziru Chen, Shijie Chen, Yuting Ning, et al.*2024 · 81 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-scienceagentbench-rigorous-assessment-language/)
15. [**BioMedLM: A 2.7B Parameter Language Model Trained On Biomedical Text arXiv:2403.18421**Elliot Bolton, Abhinav Venigalla, Michihiro Yasunaga, et al.*2024 · 79 citations*](https://md.research.elamur.ai/free/en/papers/bolton-2024-biomedlm-2-7b-parameter-language/)
16. [**Benchmarking Benchmark Leakage in Large Language Models arXiv:2404.18824**Ruijie Xu, Zengzhi Wang, Run-Ze Fan, et al.*2024 · 73 citations*](https://md.research.elamur.ai/free/en/papers/xu-2024-benchmarking-benchmark-leakage-large-language/)
17. [**A Comprehensive Survey on Long Context Language Modeling arXiv:2503.17407**Jiaheng Liu, Dawei Zhu, Zhiqi Bai, et al.*2025 · 64 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-comprehensive-survey-long-context-language/)
18. **[Unintended Impacts of LLM Alignment on Global Representation](https://md.research.elamur.ai/free/en/papers/ryan-2024-unintended-impacts-llm-alignment-global/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Michael J Ryan, William Held, Diyi Yang*2024 · 57 citations*
19. [**Magentic-One: A Generalist Multi-Agent System for Solving Complex Tasks arXiv:2411.04468**Adam Fourney, Gagan Bansal, Hussein Mozannar, et al.*2024 · 54 citations*](https://md.research.elamur.ai/free/en/papers/fourney-2024-magentic-one-generalist-multi/)
20. [**RLEF: Grounding Code LLMs in Execution Feedback with Reinforcement Learning arXiv:2410.02089**Jonas Gehring, Kunhao Zheng, Jade Copet, et al.*2024 · 51 citations*](https://md.research.elamur.ai/free/en/papers/gehring-2024-rlef-grounding-code-llms-execution/)
21. [**MLGym: A New Framework and Benchmark for Advancing AI Research Agents arXiv:2502.14499**Deepak Nathani, Lovish Madaan, Nicholas Roberts, et al.*2025 · 50 citations*](https://md.research.elamur.ai/free/en/papers/nathani-2025-mlgym-new-framework-benchmark/)
22. [**ClimateGPT: Towards AI Synthesizing Interdisciplinary Research on Climate Change arXiv:2401.09646**David Thulke, Yingbo Gao, Petrus Pelser, et al.*2024 · 45 citations*](https://md.research.elamur.ai/free/en/papers/thulke-2024-climategpt-towards-ai-synthesizing-interdisciplinary/)
23. [**A Survey of Frontiers in LLM Reasoning: Inference Scaling, Learning to Reason, and Agentic Systems arXiv:2504.09037**Zixuan Ke, Fangkai Jiao, Yifei Ming, et al.*2025 · 39 citations*](https://md.research.elamur.ai/free/en/papers/ke-2025-survey-frontiers-llm-reasoning-inference/)
24. [**LLM4SR: A Survey on Large Language Models for Scientific Research arXiv:2501.04306**Ziming Luo, Zonglin Yang, Zexin Xu, et al.*2025 · 39 citations*](https://md.research.elamur.ai/free/en/papers/luo-2025-llm4sr-survey-large-language/)
25. [**CORE-Bench: Fostering the Credibility of Published Research Through a Computational Reproducibility Agent Benchmark arXiv:2409.11363**Zachary S. Siegel, Sayash Kapoor, Nitya Nadgir, et al.*2024 · 39 citations*](https://md.research.elamur.ai/free/en/papers/siegel-2024-core-bench-fostering-credibility/)
26. [**Introducing v0.5 of the AI Safety Benchmark from MLCommons arXiv:2404.12241**Bertie Vidgen, Adarsh Agrawal, Ahmed M. Ahmed, et al.*2024 · 38 citations*](https://md.research.elamur.ai/free/en/papers/vidgen-2024-introducing-v0-5-ai-safety/)
27. [**Scaling of Search and Learning: A Roadmap to Reproduce o1 from Reinforcement Learning Perspective arXiv:2412.14135**Zhiyuan Zeng, Qinyuan Cheng, Zhangyue Yin, et al.*2024 · 33 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2024-scaling-search-learning-roadmap-reproduce/)
28. [**Jamba-1.5: Hybrid Transformer-Mamba Models at Scale arXiv:2408.12570**Jamba Team: Barak Lenz, Alan Arazi, Amir Bergman, et al.*2024 · 30 citations*](https://md.research.elamur.ai/free/en/papers/lenz-2024-jamba-1-5-hybrid-transformer/)
29. **[The State of Multilingual LLM Safety Research: From Measuring The Language Gap To Mitigating It](https://md.research.elamur.ai/free/en/papers/yong-2025-state-multilingual-llm-safety-research/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zheng Xin Yong, Beyza Ermis, Marzieh Fadaee, et al.*2025 · 25 citations*
30. [**Towards Scientific Intelligence: A Survey of LLM-based Scientific Agents arXiv:2503.24047**Shuo Ren, Can Xie, Pu Jian, et al.*2025 · 24 citations*](https://md.research.elamur.ai/free/en/papers/ren-2025-scientific-intelligence-survey-llm/)
31. [**SciReplicate-Bench: Benchmarking LLMs in Agent-driven Algorithmic Reproduction from Research Papers arXiv:2504.00255**Yanzheng Xiang, Hanqi Yan, Shuyin Ouyang, et al.*2025 · 23 citations*](https://md.research.elamur.ai/free/en/papers/xiang-2025-scireplicate-bench-benchmarking-llms/)
32. **[The Leaderboard Illusion](https://md.research.elamur.ai/free/en/papers/singh-2025-leaderboard-illusion/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Shivalika Singh, Yiyang Nan, Alex Wang, et al.*2025 · 22 citations*
33. **[A Survey on Evaluation of LLM-based Agents](https://md.research.elamur.ai/free/en/papers/yehudai-2026-survey-evaluation-llm-based-agents/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Asaf Yehudai, Lilach Eden, Alan Li, et al.*2026 · 21 citations*
34. [**The Limits of Inference Scaling Through Resampling arXiv:2411.17501**Benedikt Stroebl, Sayash Kapoor, Arvind Narayanan*2024 · 21 citations*](https://md.research.elamur.ai/free/en/papers/stroebl-2024-limits-inference-scaling-through-resampling/)
35. [**AstaBench: Rigorous Benchmarking of AI Agents with a Scientific Research Suite arXiv:2510.21652**Jonathan Bragg, Mike D'Arcy, Nishant Balepur, et al.*2025 · 19 citations*](https://md.research.elamur.ai/free/en/papers/bragg-2025-astabench-rigorous-benchmarking-ai-agents/)
36. **[ResearchCodeBench: Benchmarking LLMs on Implementing Novel Machine Learning Research Code](https://md.research.elamur.ai/free/en/papers/hua-2025-researchcodebench-benchmarking-llms-implementing/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Tianyu Hua; Harper Hua; Violet Xiang; Benjamin Klieger; Sang T. Truong; Weixin Liang; Fan-Yun Sun;, Nick Haber*2025 · 16 citations*
37. **[MLRC-Bench: Can Language Agents Solve Machine Learning Research Challenges?](https://md.research.elamur.ai/free/en/papers/zhang-2025-mlrc-bench-language-agents/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yunxiang Zhang, Muhammad Khalifa, Shitanshu Bhushan, et al.*2025 · 13 citations*
38. [**When AI Co-Scientists Fail: SPOT-a Benchmark for Automated Verification of Scientific Research arXiv:2505.11855**Guijin Son, Jiwoo Hong, Honglu Fan, et al.*2025 · 13 citations*](https://md.research.elamur.ai/free/en/papers/son-2025-ai-co-scientists-fail/)
39. [**AI Scientists Fail Without Strong Implementation Capability arXiv:2506.01372**Minjun Zhu, Qiujie Xie, Yixuan Weng, et al.*2025 · 12 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2025-ai-scientists-fail-strong/)
40. **[AutoReproduce: Automatic AI Experiment Reproduction with Paper Lineage](https://md.research.elamur.ai/free/en/papers/zhao-2025-autoreproduce-automatic-ai-experiment/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xuanle Zhao, Zilin Sang, Yuxuan Li, et al.*2025 · 12 citations*
41. [**TRAIL: Trace Reasoning and Agentic Issue Localization arXiv:2505.08638**Darshan Deshpande, Varun Gangal, Hersh Mehta, et al.*2025 · 12 citations*](https://md.research.elamur.ai/free/en/papers/deshpande-2025-trail-trace-reasoning-agentic-issue/)
42. [**Holistic Agent Leaderboard: The Missing Infrastructure for AI Agent Evaluation arXiv:2510.11977**Sayash Kapoor, Benedikt Stroebl, Peter Kirgis, et al.*2025 · 11 citations*](https://md.research.elamur.ai/free/en/papers/kapoor-2025-holistic-agent-leaderboard-missing/)
43. **[SciArena: An Open Evaluation Platform for Non-Verifiable Scientific Literature-Grounded Tasks](https://md.research.elamur.ai/free/en/papers/zhao-2025-sciarena-open-evaluation-platform-non/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yilun Zhao, Kaiyan Zhang, Tiansheng Hu, et al.*2025 · 11 citations*
44. **[Examining False Positives under Inference Scaling for Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/wang-2025-examining-false-positives-under-inference/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yu Wang, Nan Yang, Liang Wang, et al.*2025 · 9 citations*
45. [**SafeScientist: Toward Risk-Aware Scientific Discoveries by LLM Agents arXiv:2505.23559**Kunlun Zhu, Jiaxun Zhang, Ziheng Qi, et al.*2025 · 8 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2025-safescientist-toward-risk-aware-scientific/)
46. **[Localized Cultural Knowledge is Conserved and Controllable in Large Language Models](https://md.research.elamur.ai/free/en/papers/veselovsky-2026-localized-cultural-knowledge-is-conserved/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Veniamin Veselovsky, Berke Argın, Benedikt Stroebl, et al.*2026 · 7 citations*
47. **[Scaling Collaborative Effort with Agents](https://md.research.elamur.ai/free/en/papers/shen-2026-scaling-collaborative-effort-agents/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shannon Zejiang Shen, Valerie Chen, Ken Gu, et al.*2026 · 7 citations*
48. **[When Life Gives You Samples: The Benefits of Scaling up Inference Compute for Multilingual LLMs](https://md.research.elamur.ai/free/en/papers/khairi-2025-when-life-gives-you-samples/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ammar Khairi, Daniel D'souza, Ye Shen, et al.*2025 · 6 citations*
49. **[A Study of LLMs' Preferences for Libraries and Programming Languages](https://md.research.elamur.ai/free/en/papers/twist-2026-study-llms-preferences-libraries-programming/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Lukas Twist, Mark Harman, Don Syme, et al.*2026 · 5 citations*
50. [**How Far Are We From True Auto-Research? arXiv:2605.19156**Zhengxin Zhang, Ning Wang, Sainyam Galhotra, et al.*2026 · 5 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2026-far-true-auto-research/)
51. **[Lost in Simulation: LLM-Simulated Users are Unreliable Proxies for Human Users in Agentic Evaluations](https://md.research.elamur.ai/free/en/papers/seshadri-2026-lost-simulation-llm-simulated-users/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Preethi Seshadri, Samuel Cahyawijaya, Ayomide Odumakinde, et al.*2026 · 5 citations*
52. **[HiddenGuard: Fine-Grained Safe Generation with Specialized Representation Router](https://md.research.elamur.ai/free/en/papers/mei-2026-hiddenguard-fine-grained-safe-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lingrui Mei, Shenghua Liu, Yiwei Wang, et al.*2026 · 4 citations*
53. **[Uncertainty Quantification in LLM Agents: Foundations, Emerging Challenges, and Opportunities](https://md.research.elamur.ai/free/en/papers/oh-2026-uncertainty-quantification-llm-agents-foundations/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Changdae Oh, Seongheon Park, To Eun Kim, et al.*2026 · 4 citations*
54. [**Debate Only When Necessary: Adaptive Multiagent Collaboration for Efficient LLM Reasoning arXiv:2504.05047**Sugyeong Eo, Hyeonseok Moon, Evelyn Hayoon Zi, et al.*2025 · 4 citations*](https://md.research.elamur.ai/free/en/papers/eo-2025-debate-only-necessary-adaptive-multiagent/)
55. **[The Automated LLM Speedrunning Benchmark: Reproducing NanoGPT Improvements](https://md.research.elamur.ai/free/en/papers/zhao-2025-automated-llm-speedrunning-benchmark/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Bingchen Zhao, Despoina Magka, Minqi Jiang, et al.*2025 · 4 citations*
56. **[Position: LLM Watermarking Should Align Stakeholders' Incentives for Practical Adoption](https://md.research.elamur.ai/free/en/papers/liu-2026-position-llm-watermarking-should-align/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yepeng Liu, Xuandong Zhao, Dawn Song, et al.*2026 · 2 citations*
57. [**Training AI Scientists to Replicate Research arXiv:2608.13331**Damon Falck, Samer Sabri, Anja Surina, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/falck-2026-training-ai-scientists-replicate/)
58. **[In-Distribution Steering: Balancing Control and Coherence in Language Model Generation](https://md.research.elamur.ai/free/en/papers/vogels-2026-distribution-steering-balancing-control-coherence/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Arthur Vogels, Benjamin Wong, Yann Choho, et al.*2026 · 1 citation*
59. [**MÖVE: A Holistic LLM Benchmark for the German Public Sector arXiv:2606.13111**Camilla Dalerci, Thilo Michael, Robin Schaefer, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/dalerci-2026-m-ove-holistic-llm-benchmark/)
60. **[Agentic CLEAR: Automating Multi-Level Evaluation of LLM Agents](https://md.research.elamur.ai/free/en/papers/yehudai-2026-agentic-clear-automating-multi-level/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Asaf Yehudai, Lilach Eden, Michal Shmueli-Scheuer*2026*
61. **[Efficient Agent Evaluation via Diversity-Guided User Simulation](https://md.research.elamur.ai/free/en/papers/nakash-2026-efficient-agent-evaluation-diversity-guided/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Itay Nakash, George Kour, Ateret Anaby Tavor*2026*
62. **[Follow the Path: Reasoning over Knowledge Graph Paths to Improve Large Language Model Factuality](https://md.research.elamur.ai/free/en/papers/zhang-2026-follow-path-reasoning-over-knowledge/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mike Zhang, Johannes Bjerva, Russa Biswas*2026*
63. **[NLG Evaluation: Past, Present, Future](https://md.research.elamur.ai/free/en/papers/reiter-2026-nlg-evaluation-past-present-future/) [Symposium on Natural Language Generation Evaluations](https://md.research.elamur.ai/free/en/venues/retroeval/)**Ehud Reiter*2026*
64. [**The Past and Future of AI Scientists arXiv:2608.14407**Ross D. King*2026*](https://md.research.elamur.ai/free/en/papers/king-2026-past-future-ai-scientists/)
65. **[What Moves the Pareto Frontier in Tool-Using Agents? A Compute-Aware Study of ReAct Variants](https://md.research.elamur.ai/free/en/papers/simhadri-2026-what-moves-pareto-frontier-tool/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Rishi N. Simhadri*2026*
66. [**Tracr-Injection: Distilling Algorithms into Pre-trained Language Models arXiv:2505.10719**Tomás Vergara-Browne, Álvaro Soto*2025*](https://md.research.elamur.ai/free/en/papers/vergara-browne-2025-tracr-injection-distilling-algorithms/)

156 more citing papers of our library have no page here yet.

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