---
title: "Who cites Nitya Nadgir — 85 papers of our library"
description: "85 papers of the Elamur Research library cite the works of Nitya Nadgir, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/nitya-nadgir/cited-by/"
---
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# 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](https://md.research.elamur.ai/free/en/authors/nitya-nadgir/)

1. [**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/)
2. [**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/)
3. [**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/)
4. [**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/)
5. [**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/)
6. [**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/)
7. [**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/)
8. [**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/)
9. [**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/)
10. [**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/)
11. [**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/)
12. [**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/)
13. [**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/)
14. **[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*
15. [**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/)
16. [**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/)
17. **[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*
18. **[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*
19. [**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/)
20. [**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/)
21. **[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*
22. [**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/)
23. [**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/)
24. **[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*
25. [**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/)
26. **[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*
27. [**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/)
28. **[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*
29. [**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/)
30. **[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*
31. **[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*
32. **[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*

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

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