Who cites Jiakang Yuan
- Towards Scientific Intelligence: A Survey of LLM-based Scientific AgentsarXiv:2503.24047Shuo Ren, Can Xie, Pu Jian, et al.2025 · 24 citations
- AI4Research: A Survey of Artificial Intelligence for Scientific ResearchScience China Information SciencesQiguang Chen, Mingda Yang, Libo Qin, et al.2025 · 21 citations
- InternAgent: When Agent Becomes the Scientist — Building Closed-Loop System from Hypothesis to VerificationarXiv:2505.16938InternAgent Team, Bo Zhang, Shiyang Feng, et al.2025 · 21 citations
- Curie: Toward Rigorous and Automated Scientific Experimentation with AI AgentsarXiv:2502.16069Patrick Tser Jern Kon, Jiachen Liu, Qiuyi Ding, et al.2025 · 20 citations
- SURVEYFORGE : On the Outline Heuristics, Memory-Driven Generation, and Multi-dimensional Evaluation for Automated Survey WritingAnnual Meeting of the Association for Computational Linguistics (ACL)Xiangchao Yan, Shiyang Feng, Jiakang Yuan, et al.2025 · 20 citations
- Dolphin: Moving Towards Closed-loop Auto-research through Thinking, Practice, and FeedbackarXiv:2501.03916Jiakang Yuan, Xiangchao Yan, Shiyang Feng, et al.2025 · 19 citations
- 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
- 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
- AI Scientists Fail Without Strong Implementation CapabilityarXiv:2506.01372Minjun Zhu, Qiujie Xie, Yixuan Weng, et al.2025 · 12 citations
- EvoScientist: Towards Multi-Agent Evolving AI Scientists for End-to-End Scientific DiscoveryarXiv:2603.08127Yougang Lyu, Xi Zhang, Xinhao Yi, et al.2026 · 10 citations
- SafeScientist: Toward Risk-Aware Scientific Discoveries by LLM AgentsarXiv:2505.23559Kunlun Zhu, Jiaxun Zhang, Ziheng Qi, et al.2025 · 8 citations
- InnovatorBench: Evaluating Agents' Ability to Conduct Innovative LLM ResearcharXiv:2510.27598Yunze Wu, Dayuan Fu, Weiye Si, et al.2025 · 6 citations
- AI for Auto-Research: Roadmap & User GuidearXiv:2605.18661Lingdong Kong, Xian Sun, Wei Chow, et al.2026 · 5 citations
- 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
- 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
- AiraXiv: An AI-Driven Open-Access Platform for Human and AI ScientistsAnnual Meeting of the Association for Computational Linguistics (ACL)Junshu Pan, Panzhong Lu, Yixuan Weng, et al.2026 · 1 citation
- Easy Samples Are All You Need: Self-Evolving LLMs via Data-Efficient Reinforcement LearningFindings of the Association for Computational LinguisticsZhiyin Yu, Bo Zhang, Qibin Hou, et al.2026 · 1 citation
- A Survey of Reinforcement Learning for Large Language Models under Data Scarcity: Challenges and SolutionsAnnual Meeting of the Association for Computational Linguistics (ACL)Zhiyin Yu, Yuchen Mou, Juncheng Yan, et al.2026
- Feedback Is The Key for Automated Survey GenerationFindings of the Association for Computational LinguisticsTianyi Xu, Zhe Zhao, Tianshuo Wei, et al.2026
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