--- title: "Who cites RE-Bench: Evaluating frontier AI — 44 citing papers" description: "44 papers of the Elamur Research library cite «RE-Bench: Evaluating frontier AI R&D capabilities of language model agents against human…" canonical: "https://research.elamur.ai/free/en/papers/wijk-2024-re-bench-evaluating-frontier/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/wijk-2024-re-bench-evaluating-frontier/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [RE-Bench: Evaluating frontier AI R&D capabilities…](https://md.research.elamur.ai/free/en/papers/wijk-2024-re-bench-evaluating-frontier/) / cited by # 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»](https://md.research.elamur.ai/free/en/papers/wijk-2024-re-bench-evaluating-frontier/) 1. [**Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities arXiv:2507.06261**Gheorghe Comanici, Eric Bieber, Mike Schaekermann, et al.*2025 · 974 citations*](https://md.research.elamur.ai/free/en/papers/comanici-2025-gemini-2-5-pushing-frontier/) 2. **[Large Language Models for Information Retrieval: A Survey](https://md.research.elamur.ai/free/en/papers/zhu-2023-large-language-models-information-retrieval/) [ACM Transactions on Information Systems](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-information-systems/)**Yutao Zhu; Huaying Yuan; Shuting Wang; Jiongnan Liu; Wenhan Liu; Chenlong Deng; Haonan Chen; Zheng Liu; Zhicheng Dou;, Ji-Rong Wen*2023 · 339 citations* 3. **[Humanity's Last Exam](https://md.research.elamur.ai/free/en/papers/phan-2025-humanity-s-last-exam/) [Nature](https://md.research.elamur.ai/free/en/venues/nature/)**Long Phan, Alice Gatti, Ziwen Han, et al.*2025 · 256 citations* 4. [**KernelBench: Can LLMs Write Efficient GPU Kernels? arXiv:2502.10517**Anne Ouyang, Simon Guo, Simran Arora, et al.*2025 · 178 citations*](https://md.research.elamur.ai/free/en/papers/ouyang-2025-kernelbench-llms-write-efficient-gpu/) 5. [**The AI Scientist-v2: Workshop-Level Automated Scientific Discovery via Agentic Tree Search arXiv:2504.08066**Yutaro Yamada, Robert Tjarko Lange, Cong Lu, et al.*2025 · 129 citations*](https://md.research.elamur.ai/free/en/papers/yamada-2025-ai-scientist-v2-workshop/) 6. [**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/) 7. [**Chain-of-Thought Reasoning In The Wild Is Not Always Faithful arXiv:2503.08679**Ivan Arcuschin, Jett Janiak, Robert Krzyzanowski, et al.*2025 · 52 citations*](https://md.research.elamur.ai/free/en/papers/arcuschin-2025-chain-thought-reasoning-wild-always/) 8. **[From Automation to Autonomy: A Survey on Large Language Models in Scientific Discovery](https://md.research.elamur.ai/free/en/papers/zheng-2025-automation-autonomy-survey-large/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tianshi Zheng, Zheye Deng, Hong Ting Tsang, et al.*2025 · 39 citations* 9. **[Measuring AI Ability to Complete Long Software Tasks](https://md.research.elamur.ai/free/en/papers/kwa-2025-measuring-ai-ability-complete/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Thomas Kwa, Ben West, Joel Becker, et al.*2025 · 36 citations* 10. **[MLR-Bench: Evaluating AI Agents on Open-Ended Machine Learning Research](https://md.research.elamur.ai/free/en/papers/chen-2025-mlr-bench-evaluating-ai/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**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:2502.15657**Yoshua Bengio, Michael Cohen, Damiano Fornasiere, et al.*2025 · 16 citations*](https://md.research.elamur.ai/free/en/papers/bengio-2025-superintelligent-agents-pose-catastrophic-risks/) 12. **[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* 13. [**InnovatorBench: Evaluating Agents' Ability to Conduct Innovative LLM Research arXiv:2510.27598**Yunze Wu, Dayuan Fu, Weiye Si, et al.*2025 · 6 citations*](https://md.research.elamur.ai/free/en/papers/wu-2025-innovatorbench-evaluating-agents-ability-conduct/) 14. [**Training AI Co-Scientists Using Rubric Rewards arXiv:2512.23707**Shashwat Goel, Rishi Hazra, Dulhan Jayalath, et al.*2025 · 6 citations*](https://md.research.elamur.ai/free/en/papers/goel-2025-training-ai-co-scientists/) 15. [**AI for Auto-Research: Roadmap & User Guide arXiv:2605.18661**Lingdong Kong, Xian Sun, Wei Chow, et al.*2026 · 5 citations*](https://md.research.elamur.ai/free/en/papers/kong-2026-ai-auto-research-roadmap-user/) 16. [**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/) 17. **[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* 18. [**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/) 26 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/wijk-2024-re-bench-evaluating-frontier/) — RE-Bench: Evaluating frontier AI R&D capabilities of language model agents against human experts