🔗 Who cites «AIDE: AI-Driven Exploration in the Space of Code»

46 papers of our library cite it (of the 149,439 whose bibliographies we read) · 20 with a page here, the most cited first · ← back to «AIDE: AI-Driven Exploration in the Space of Code»

1. 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
2. ShinkaEvolve: Towards Open-Ended And Sample-Efficient Program EvolutionarXiv:2509.19349Robert Tjarko Lange, Yuki Imajuku, Edoardo Cetin2025 · 42 citations
3. 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
4. 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
5. An AI system to help scientists write expert-level empirical softwareNatureEser Aygün, Anastasiya Belyaeva, Gheorghe Comanici, et al.2025 · 27 citations
6. 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
7. 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
8. AI Scientists Fail Without Strong Implementation CapabilityarXiv:2506.01372Minjun Zhu, Qiujie Xie, Yixuan Weng, et al.2025 · 12 citations
9. LMR-BENCH: Evaluating LLM Agent's Ability on Reproducing Language Modeling ResearcharXiv:2506.17335Shuo Yan, Ruochen Li, Ziming Luo, et al.2025 · 12 citations
10. AI for Auto-Research: Roadmap & User GuidearXiv:2605.18661Lingdong Kong, Xian Sun, Wei Chow, et al.2026 · 5 citations
11. 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
12. SPIO: Ensemble and Selective Strategies via LLM-Based Multi-Agent Planning in Automated Data ScienceAnnual Meeting of the Association for Computational Linguistics (ACL)Wonduk Seo, Juhyeon Lee, Yanjun Shao, et al.2026 · 3 citations
13. Can We Predict Before Executing Machine Learning Agents?Annual Meeting of the Association for Computational Linguistics (ACL)Jingsheng Zheng, Jintian Zhang, Yujie Luo, et al.2026 · 2 citations
14. Learning to Ideate for Machine Learning Engineering AgentsConference of the European Chapter of the Association for Computational Linguistics (EACL)Yunxiang Zhang, Kang Zhou, Zhichao Xu, et al.2026 · 2 citations
15. Timely Machine: Awareness of Time Makes Test-Time Scaling AgenticAnnual Meeting of the Association for Computational Linguistics (ACL)Yichuan Ma, Linyang Li, Yongkang Chen, et al.2026 · 2 citations
16. Training AI Scientists to Replicate ResearcharXiv:2608.13331Damon Falck, Samer Sabri, Anja Surina, et al.2026 · 2 citations
17. Demystify the Role of Memory in Machine Learning Engineering AgentsFindings of the Association for Computational LinguisticsXinyu Zhao, Junpeng Wang, Yuzhong Chen, et al.2026
18. DSMentor: Curriculum-Guided Inference with Online Memory for Data-Science LLM AgentsWorkshop on Structured Understanding, Retrieval, and Generation in the LLM EraHe Wang, Alexander Hanbo Li, Yiqun Hu, et al.2026
19. Reasoning as Gradient: Scaling MLE Agents Beyond Tree SearchFindings of the Association for Computational LinguisticsYifei Zhang, Xu Yang, Xiao Yang, et al.2026
20. Survey on Code Generation with LLM-based Agents (基于大语言模型智能体的代码生成综述)Journal of SoftwareYihong Dong (董益宏), Xue Jiang (姜雪), Jiaru Qian (钱家如), et al.2025

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

↑ back to top

This page in Markdown → https://md.research.elamur.ai/free/en/papers/jiang-2025-aide-ai-driven-exploration/cited-by/