🔗 Who cites «CodeScientist: End-to-End Semi-Automated Scientific Discovery with Code-based Experimentation»

29 papers of our library cite it (of the 149,439 whose bibliographies we read) · 12 with a page here, the most cited first · ← back to «CodeScientist: End-to-End Semi-Automated Scientific Discovery with Code-based Experimentation»

1. MLR-Copilot: Autonomous Machine Learning Research based on Large Language Models AgentsarXiv:2408.14033Ruochen Li, Teerth Patel, Qingyun Wang, et al.2024 · 43 citations
2. 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
3. Transforming Science with Large Language Models: A Survey on AI-assisted Scientific Discovery, Experimentation, Content Generation, and EvaluationACM Computing SurveysSteffen Eger, Yong Cao, Jennifer D'Souza, et al.2025 · 25 citations
4. AstaBench: Rigorous Benchmarking of AI Agents with a Scientific Research SuitearXiv:2510.21652Jonathan Bragg, Mike D'Arcy, Nishant Balepur, et al.2025 · 19 citations
5. From AI for Science to Agentic Science: A Survey on Autonomous Scientific DiscoveryarXiv:2508.14111Jiaqi Wei, Yuejin Yang, Xiang Zhang, et al.2025 · 19 citations
6. AI Scientists Fail Without Strong Implementation CapabilityarXiv:2506.01372Minjun Zhu, Qiujie Xie, Yixuan Weng, et al.2025 · 12 citations
7. LMR-BENCH: Evaluating LLM Agent's Ability on Reproducing Language Modeling ResearcharXiv:2506.17335Shuo Yan, Ruochen Li, Ziming Luo, et al.2025 · 12 citations
8. Language Modeling by Language ModelsConference on Neural Information Processing Systems (NeurIPS)Junyan Cheng, Peter Clark, Kyle Richardson2025 · 9 citations
9. AI for Auto-Research: Roadmap & User GuidearXiv:2605.18661Lingdong Kong, Xian Sun, Wei Chow, et al.2026 · 5 citations
10. FARS: A Fully Automated Research System Deployed at ScalearXiv:2606.31651Qiong Tang, Tianxiang Sun, Xiangkun Hu, et al.2026 · 1 citation
11. EvoSci: A Bio-Inspired Multi-Agent Framework for the Evolution of Scientific DiscoveryAnnual Meeting of the Association for Computational Linguistics (ACL)Xiaoyu Xiong, Yuqi Ren, Deyi Xiong2026
12. OptiVerse: A Comprehensive Benchmark towards Optimization Problem SolvingFindings of the Association for Computational LinguisticsXinyu Zhang, Boxuan Zhang, Yuchen Wan, et al.2026

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

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