🔗 Who cites «RE-Bench: Evaluating frontier AI R&D capabilities of language model agents against human experts»

44 papers of our library cite it (of the 149,439 whose bibliographies we read) · 18 with a page here, the most cited first · ← back to «RE-Bench: Evaluating frontier AI R&D capabilities of language model agents against human experts»

1. Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic CapabilitiesarXiv:2507.06261Gheorghe Comanici, Eric Bieber, Mike Schaekermann, et al.2025 · 974 citations
2. Large Language Models for Information Retrieval: A SurveyACM Transactions on Information SystemsYutao Zhu; Huaying Yuan; Shuting Wang; Jiongnan Liu; Wenhan Liu; Chenlong Deng; Haonan Chen; Zheng Liu; Zhicheng Dou;, Ji-Rong Wen2023 · 339 citations
3. Humanity's Last ExamNatureLong Phan, Alice Gatti, Ziwen Han, et al.2025 · 256 citations
4. KernelBench: Can LLMs Write Efficient GPU Kernels?arXiv:2502.10517Anne Ouyang, Simon Guo, Simran Arora, et al.2025 · 178 citations
5. The AI Scientist-v2: Workshop-Level Automated Scientific Discovery via Agentic Tree SearcharXiv:2504.08066Yutaro Yamada, Robert Tjarko Lange, Cong Lu, et al.2025 · 129 citations
6. PaperBench: Evaluating AI's Ability to Replicate AI ResearcharXiv:2504.01848Giulio Starace, Oliver Jaffe, Dane Sherburn, et al.2025 · 86 citations
7. Chain-of-Thought Reasoning In The Wild Is Not Always FaithfularXiv:2503.08679Ivan Arcuschin, Jett Janiak, Robert Krzyzanowski, et al.2025 · 52 citations
8. 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
9. Measuring AI Ability to Complete Long Software TasksConference on Neural Information Processing Systems (NeurIPS)Thomas Kwa, Ben West, Joel Becker, et al.2025 · 36 citations
10. 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
11. Superintelligent Agents Pose Catastrophic Risks: Can Scientist AI Offer a Safer Path?arXiv:2502.15657Yoshua Bengio, Michael Cohen, Damiano Fornasiere, et al.2025 · 16 citations
12. 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
13. InnovatorBench: Evaluating Agents' Ability to Conduct Innovative LLM ResearcharXiv:2510.27598Yunze Wu, Dayuan Fu, Weiye Si, et al.2025 · 6 citations
14. Training AI Co-Scientists Using Rubric RewardsarXiv:2512.23707Shashwat Goel, Rishi Hazra, Dulhan Jayalath, et al.2025 · 6 citations
15. AI for Auto-Research: Roadmap & User GuidearXiv:2605.18661Lingdong Kong, Xian Sun, Wei Chow, et al.2026 · 5 citations
16. How Far Are We From True Auto-Research?arXiv:2605.19156Zhengxin Zhang, Ning Wang, Sainyam Galhotra, et al.2026 · 5 citations
17. 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
18. Training AI Scientists to Replicate ResearcharXiv:2608.13331Damon Falck, Samer Sabri, Anja Surina, et al.2026 · 2 citations

26 more papers of our library cite it; they have no page here yet.

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