--- title: "Who cites CORE-Bench: Fostering the — 35 citing papers" description: "35 papers of the Elamur Research library cite «CORE-Bench: Fostering the Credibility of Published Research Through a Computational…" canonical: "https://research.elamur.ai/free/en/papers/siegel-2024-core-bench-fostering-credibility/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/siegel-2024-core-bench-fostering-credibility/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [CORE-Bench: Fostering the Credibility of…](https://md.research.elamur.ai/free/en/papers/siegel-2024-core-bench-fostering-credibility/) / cited by # Who cites «CORE-Bench: Fostering the Credibility of Published Research Through a Computational Reproducibility Agent Benchmark» 35 papers of our library cite it (of the 149,439 whose bibliographies we read) · 15 with a page here, the most cited first · [← back to «CORE-Bench: Fostering the Credibility of Published Research Through a Computational Reproducibility Agent Benchmark»](https://md.research.elamur.ai/free/en/papers/siegel-2024-core-bench-fostering-credibility/) 1. [**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/) 2. [**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/) 3. [**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/) 4. [**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/) 5. **[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* 6. [**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/) 7. **[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* 8. [**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/) 9. [**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/) 10. **[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* 11. [**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/) 12. [**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/) 13. **[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* 14. **[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* 15. [**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/) 20 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/siegel-2024-core-bench-fostering-credibility/) — CORE-Bench: Fostering the Credibility of Published Research Through a Computational Reproducibility Agent Benchmark