🧑‍🔬 Who cites Ying Wen

102 citations of their works from 100 papers of our library (of the 149,439 whose bibliographies we read) · 44 with a page here, the most cited first · ← Ying Wen

1. Can LLMs Generate Novel Research Ideas? A Large-Scale Human Study with 100+ NLP ResearchersarXiv:2409.04109Chenglei Si, Diyi Yang, Tatsunori Hashimoto2024 · 196 citations
2. Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language ModelsScience China Information SciencesQiguang Chen, Libo Qin, Jinhao Liu, et al.2025 · 176 citations
3. Agent Laboratory: Using LLM Agents as Research AssistantsarXiv:2501.04227Samuel Schmidgall, Yusheng Su, Ze Wang, et al.2025 · 139 citations
4. Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language ModelsarXiv:2501.09686Fengli Xu, Qianyue Hao, Zefang Zong, et al.2025 · 120 citations
5. Data Interpreter: An LLM Agent for Data ScienceFindings of the Association for Computational LinguisticsSirui Hong, Yizhang Lin, Bang Liu, et al.2025 · 91 citations
6. HuatuoGPT-o1, Towards Medical Complex Reasoning with LLMsarXiv:2412.18925Junying Chen, Zhenyang Cai, Ke Ji, et al.2024 · 87 citations
7. A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?arXiv:2503.24235Qiyuan Zhang, Fuyuan Lyu, Zexu Sun, et al.2025 · 79 citations
8. Spurious Rewards: Rethinking Training Signals in RLVRarXiv:2506.10947Rulin Shao, Shuyue Stella Li, Rui Xin, et al.2025 · 53 citations
9. Agent-as-a-Judge: Evaluate Agents with AgentsarXiv:2410.10934Mingchen Zhuge, Changsheng Zhao, Dylan Ashley, et al.2024 · 50 citations
10. RE-Bench: Evaluating frontier AI R&D capabilities of language model agents against human expertsarXiv:2411.15114Hjalmar Wijk, Tao Lin, Joel Becker, et al.2024 · 46 citations
11. DSBench: How Far Are Data Science Agents from Becoming Data Science Experts?arXiv:2409.07703Liqiang Jing, Zhehui Huang, Xiaoyang Wang, et al.2024 · 44 citations
12. Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time ScalingarXiv:2502.06703Runze Liu, Junqi Gao, Jian Zhao, et al.2025 · 41 citations
13. AgentRxiv: Towards Collaborative Autonomous ResearcharXiv:2503.18102Samuel Schmidgall, Michael Moor2025 · 39 citations
14. 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
15. Revisiting the Test-Time Scaling of o1-like Models: Do they Truly Possess Test-Time Scaling Capabilities?Annual Meeting of the Association for Computational Linguistics (ACL)Zhiyuan Zeng, Qinyuan Cheng, Zhangyue Yin, et al.2025 · 38 citations
16. Scaling of Search and Learning: A Roadmap to Reproduce o1 from Reinforcement Learning PerspectivearXiv:2412.14135Zhiyuan Zeng, Qinyuan Cheng, Zhangyue Yin, et al.2024 · 33 citations
17. AI4Research: A Survey of Artificial Intelligence for Scientific ResearchScience China Information SciencesQiguang Chen, Mingda Yang, Libo Qin, et al.2025 · 21 citations
18. 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
19. R-PRM: Reasoning-Driven Process Reward ModelingConference on Empirical Methods in Natural Language Processing (EMNLP)Shuaijie She, Junxiao Liu, Yifeng Liu, et al.2025 · 18 citations
20. Aviary: training language agents on challenging scientific tasksarXiv:2412.21154Siddharth Narayanan, James D. Braza, Ryan-Rhys Griffiths, et al.2024 · 18 citations
21. EXP-Bench: Can AI Conduct AI Research Experiments?arXiv:2505.24785Patrick Tser Jern Kon, Jiachen Liu, Xinyi Zhu, et al.2025 · 17 citations
22. CodePRM: Execution Feedback-enhanced Process Reward Model for Code GenerationFindings of the Association for Computational LinguisticsQingyao Li, Xinyi Dai, Xiangyang Li, et al.2025 · 15 citations
23. AI Scientists Fail Without Strong Implementation CapabilityarXiv:2506.01372Minjun Zhu, Qiujie Xie, Yixuan Weng, et al.2025 · 12 citations
24. Literature Meets Data: A Synergistic Approach to Hypothesis GenerationAnnual Meeting of the Association for Computational Linguistics (ACL)Haokun Liu, Yangqiaoyu Zhou, Mingxuan Li, et al.2025 · 12 citations
25. Beyond Distillation: Pushing the Limits of Medical LLM Reasoning with Minimalist Rule-Based RLarXiv:2505.17952Che Liu, Haozhe Wang, Jiazhen Pan, et al.2025 · 10 citations
26. Examining False Positives under Inference Scaling for Mathematical ReasoningConference on Empirical Methods in Natural Language Processing (EMNLP)Yu Wang, Nan Yang, Liang Wang, et al.2025 · 9 citations
27. ViLBench: A Suite for Vision-Language Process Reward ModelingConference on Empirical Methods in Natural Language Processing (EMNLP)Haoqin Tu, Weitao Feng, Hardy Chen, et al.2025 · 9 citations
28. MetaScale: Test-Time Scaling with Evolving Meta-ThoughtsFindings of the Association for Computational LinguisticsQin Liu, Wenxuan Zhou, Nan Xu, et al.2026 · 7 citations
29. AI for Auto-Research: Roadmap & User GuidearXiv:2605.18661Lingdong Kong, Xian Sun, Wei Chow, et al.2026 · 5 citations
30. A Survey of AI ScientistsarXiv:2510.23045Guiyao Tie, Pan Zhou, Lichao Sun2025 · 5 citations
31. Guided by Gut: Efficient Test-Time Scaling with Reinforced Intrinsic ConfidenceAnnual Meeting of the Association for Computational Linguistics (ACL)Amirhosein Ghasemabadi, Keith G. Mills, Baochun Li, et al.2026 · 4 citations
32. MAPRO: Recasting Multi-Agent Prompt Optimization as Maximum a Posteriori InferenceFindings of the Association for Computational LinguisticsZheyuan Zhang, Lin Ge, Hongjiang Li, et al.2026 · 3 citations
33. 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
34. 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
35. MedMCP-Calc: Benchmarking LLMs for Realistic Medical Calculator Scenarios via MCP IntegrationAnnual Meeting of the Association for Computational Linguistics (ACL)Yakun Zhu, Yutong Huang, Shengqian Qin, et al.2026 · 2 citations
36. Process Reward Models Meet Planning: Generating Precise and Scalable Datasets for Step-Level RewardsAnnual Meeting of the Association for Computational Linguistics (ACL)Raffaele Pisano, Roberto Navigli2026 · 1 citation
37. A Comprehensive Survey of Process Reward Models: Data Generation, Model Construction, and UsageAnnual Meeting of the Association for Computational Linguistics (ACL)Congmin Zheng, Jiachen Zhu, Zhuoying Ou, et al.2026
38. A Survey of Large Language Model-Based Search AgentsAnnual Meeting of the Association for Computational Linguistics (ACL)Yunjia Xi, Jianghao Lin, Yongzhao Xiao, et al.2026
39. ClimAgent: LLM as Agents for Autonomous Open-ended Climate Science AnalysisFindings of the Association for Computational LinguisticsHao Wang, Jindong Han, Wei Fan, et al.2026
40. Demystify the Role of Memory in Machine Learning Engineering AgentsFindings of the Association for Computational LinguisticsXinyu Zhao, Junpeng Wang, Yuzhong Chen, et al.2026
41. 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
42. Model-Based Imaginative Planning for Embodied AgentsAnnual Meeting of the Association for Computational Linguistics (ACL)Junru Song, Hengzhe Jin, Yucong Huang, et al.2026
43. ThinkBooster: A Unified Framework for Seamless Test-Time Scaling of LLM ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Vladislav Smirnov, Quang-Chieu Nguyen, Sergey Senichev, et al.2026
44. Tree-Notebook: A Context-Aware Agent with Tree Search and Entropy-Aware Data Shadow for Interactive Data ScienceFindings of the Association for Computational LinguisticsJunkun Qiu, Min Huang, Qinghai Miao2026

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