--- title: "Who cites Xiangchao Yan — 40 papers of our library" description: "40 papers of the Elamur Research library cite the works of Xiangchao Yan, found in their bibliographies; the most cited first." canonical: "https://research.elamur.ai/free/en/authors/xiangchao-yan/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/xiangchao-yan/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Xiangchao Yan](https://md.research.elamur.ai/free/en/authors/xiangchao-yan/) / cited by # Who cites Xiangchao Yan 50 citations of their works from 40 papers of our library (of the 149,439 whose bibliographies we read) · 20 with a page here, the most cited first · [← Xiangchao Yan](https://md.research.elamur.ai/free/en/authors/xiangchao-yan/) 1. [**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/) 2. **[AI4Research: A Survey of Artificial Intelligence for Scientific Research](https://md.research.elamur.ai/free/en/papers/chen-2025-ai4research-survey-artificial-intelligence/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Mingda Yang, Libo Qin, et al.*2025 · 21 citations* 3. [**InternAgent: When Agent Becomes the Scientist — Building Closed-Loop System from Hypothesis to Verification arXiv:2505.16938**InternAgent Team, Bo Zhang, Shiyang Feng, et al.*2025 · 21 citations*](https://md.research.elamur.ai/free/en/papers/team-2025-internagent-agent-becomes-scientist/) 4. [**Curie: Toward Rigorous and Automated Scientific Experimentation with AI Agents arXiv:2502.16069**Patrick Tser Jern Kon, Jiachen Liu, Qiuyi Ding, et al.*2025 · 20 citations*](https://md.research.elamur.ai/free/en/papers/kon-2025-curie-rigorous-automated-scientific/) 5. **[SURVEYFORGE : On the Outline Heuristics, Memory-Driven Generation, and Multi-dimensional Evaluation for Automated Survey Writing](https://md.research.elamur.ai/free/en/papers/yan-2025-surveyforge-outline-heuristics-memory-driven/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiangchao Yan, Shiyang Feng, Jiakang Yuan, et al.*2025 · 20 citations* 6. [**Dolphin: Moving Towards Closed-loop Auto-research through Thinking, Practice, and Feedback arXiv:2501.03916**Jiakang Yuan, Xiangchao Yan, Shiyang Feng, et al.*2025 · 19 citations*](https://md.research.elamur.ai/free/en/papers/yuan-2025-dolphin-moving-closed-loop/) 7. [**From AI for Science to Agentic Science: A Survey on Autonomous Scientific Discovery arXiv:2508.14111**Jiaqi Wei, Yuejin Yang, Xiang Zhang, et al.*2025 · 19 citations*](https://md.research.elamur.ai/free/en/papers/wei-2025-ai-science-agentic-science/) 8. **[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* 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. [**EvoScientist: Towards Multi-Agent Evolving AI Scientists for End-to-End Scientific Discovery arXiv:2603.08127**Yougang Lyu, Xi Zhang, Xinhao Yi, et al.*2026 · 10 citations*](https://md.research.elamur.ai/free/en/papers/lyu-2026-evoscientist-towards-multi-agent-evolving/) 11. [**SafeScientist: Toward Risk-Aware Scientific Discoveries by LLM Agents arXiv:2505.23559**Kunlun Zhu, Jiaxun Zhang, Ziheng Qi, et al.*2025 · 8 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2025-safescientist-toward-risk-aware-scientific/) 12. [**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/) 13. [**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/) 14. **[Can We Predict Before Executing Machine Learning Agents?](https://md.research.elamur.ai/free/en/papers/zheng-2026-can-we-predict-before-executing/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jingsheng Zheng, Jintian Zhang, Yujie Luo, et al.*2026 · 2 citations* 15. **[Learning to Ideate for Machine Learning Engineering Agents](https://md.research.elamur.ai/free/en/papers/zhang-2026-learning-ideate-machine-learning-engineering/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Yunxiang Zhang, Kang Zhou, Zhichao Xu, et al.*2026 · 2 citations* 16. **[AiraXiv: An AI-Driven Open-Access Platform for Human and AI Scientists](https://md.research.elamur.ai/free/en/papers/pan-2026-airaxiv-ai-driven-open-access/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junshu Pan, Panzhong Lu, Yixuan Weng, et al.*2026 · 1 citation* 17. **[Easy Samples Are All You Need: Self-Evolving LLMs via Data-Efficient Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/yu-2026-easy-samples-are-all-you/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhiyin Yu, Bo Zhang, Qibin Hou, et al.*2026 · 1 citation* 18. **[A Survey of Reinforcement Learning for Large Language Models under Data Scarcity: Challenges and Solutions](https://md.research.elamur.ai/free/en/papers/yu-2026-survey-reinforcement-learning-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhiyin Yu, Yuchen Mou, Juncheng Yan, et al.*2026* 19. **[Bloom-Eval: A Hierarchical Evaluation Benchmark for Automatic Survey Generation Based on Bloom's Taxonomy](https://md.research.elamur.ai/free/en/papers/zhang-2026-bloom-eval-hierarchical-evaluation-benchmark/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Fei Zhang, Zhe Zhao, HaiBin Wen, et al.*2026* 20. **[Feedback Is The Key for Automated Survey Generation](https://md.research.elamur.ai/free/en/papers/xu-2026-feedback-is-key-automated-survey/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tianyi Xu, Zhe Zhao, Tianshuo Wei, et al.*2026* 20 more citing papers of our library have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/authors/xiangchao-yan/) — Xiangchao Yan