🧑‍🔬 Who cites Zenan Li

83 citations of their works from 75 papers of our library (of the 149,439 whose bibliographies we read) · 35 with a page here, the most cited first · ← Zenan Li

1. PutnamBench: Evaluating Neural Theorem-Provers on the Putnam Mathematical CompetitionConference on Neural Information Processing Systems (NeurIPS)George Tsoukalas, Jasper Lee, John Jennings, et al.2024 · 93 citations
2. Goedel-Prover-V2: Scaling Formal Theorem Proving with Scaffolded Data Synthesis and Self-CorrectionarXiv:2508.03613Yong Lin, Shange Tang, Bohan Lyu, et al.2025 · 67 citations
3. Lean-STaR: Learning to Interleave Thinking and ProvingarXiv:2407.10040Haohan Lin, Zhiqing Sun, Sean Welleck, et al.2024 · 51 citations
4. Formal Mathematical Reasoning: A New Frontier in AIarXiv:2412.16075Kaiyu Yang, Gabriel Poesia, Jingxuan He, et al.2024 · 49 citations
5. A Survey of Frontiers in LLM Reasoning: Inference Scaling, Learning to Reason, and Agentic SystemsarXiv:2504.09037Zixuan Ke, Fangkai Jiao, Yifei Ming, et al.2025 · 39 citations
6. Lean Copilot: Large Language Models as Copilots for Theorem Proving in LeanarXiv:2404.12534Peiyang Song, Kaiyu Yang, Anima Anandkumar2024 · 39 citations
7. Gold-medalist Performance in Solving Olympiad Geometry with AlphaGeometry2arXiv:2502.03544Yuri Chervonyi, Trieu H. Trinh, Miroslav Olšák, et al.2025 · 31 citations
8. AutoVerus: Automated Proof Generation for Rust CodeProceedings of the ACM on Programming LanguagesChenyuan Yang, Xuheng Li, Md Rakib Hossain Misu, et al.2024 · 28 citations
9. Hilbert: Recursively Building Formal Proofs with Informal ReasoningarXiv:2509.22819Sumanth Varambally, Thomas Voice, Yanchao Sun, et al.2025 · 26 citations
10. Autoformalizing Euclidean GeometryarXiv:2405.17216Logan Murphy, Kaiyu Yang, Jialiang Sun, et al.2024 · 23 citations
11. AI4Research: A Survey of Artificial Intelligence for Scientific ResearchScience China Information SciencesQiguang Chen, Mingda Yang, Libo Qin, et al.2025 · 21 citations
12. Autoformalize Mathematical Statements by Symbolic Equivalence and Semantic ConsistencyConference on Neural Information Processing Systems (NeurIPS)Zenan Li, Yifan Wu, Zhaoyu Li, et al.2024 · 19 citations
13. FormalAlign: Automated Alignment Evaluation for AutoformalizationarXiv:2410.10135Jianqiao Lu, Yingjia Wan, Yinya Huang, et al.2024 · 18 citations
14. miniCTX: Neural Theorem Proving with (Long-)ContextsarXiv:2408.03350Jiewen Hu, Thomas Zhu, Sean Welleck2024 · 18 citations
15. ATLAS: Autoformalizing Theorems through Lifting, Augmentation, and Synthesis of DataConference on Neural Information Processing Systems (NeurIPS)Xiaoyang Liu, Kangjie Bao, Jiashuo Zhang, et al.2025 · 16 citations
16. DafnyBench: A Benchmark for Formal Software VerificationarXiv:2406.08467Chloe Loughridge, Qinyi Sun, Seth Ahrenbach, et al.2024 · 15 citations
17. Autoformalization in the Era of Large Language Models: A SurveyarXiv:2505.23486Ke Weng, Lun Du, Sirui Li, et al.2025 · 11 citations
18. Autoformalization in the Wild: Assessing LLMs on Real-World Mathematical DefinitionsConference on Empirical Methods in Natural Language Processing (EMNLP)Lan Zhang, Marco Valentino, Andre Freitas2025 · 11 citations
19. Proving Olympiad Inequalities by Synergizing LLMs and Symbolic ReasoningarXiv:2502.13834Zenan Li, Zhaoyu Li, Wen Tang, et al.2025 · 11 citations
20. AlphaVerus: Bootstrapping Formally Verified Code Generation through Self-Improving Translation and TreefinementarXiv:2412.06176Pranjal Aggarwal, Bryan Parno, Sean Welleck2024 · 11 citations
21. Theorem Prover as a Judge for Synthetic Data GenerationAnnual Meeting of the Association for Computational Linguistics (ACL)Joshua Ong Jun Leang, Giwon Hong, Wenda Li, et al.2025 · 9 citations
22. LogicPro: Improving Complex Logical Reasoning via Program-Guided LearningAnnual Meeting of the Association for Computational Linguistics (ACL)Jin Jiang, Yuchen Yan, Yang Liu, et al.2025 · 8 citations
23. ReForm: Reflective Autoformalization with Prospective Bounded Sequence OptimizationarXiv:2510.24592Guoxin Chen, Jing Wu, Xinjie Chen, et al.2025 · 8 citations
24. Reviving DSP for Advanced Theorem Proving in the Era of Reasoning ModelsConference on Neural Information Processing Systems (NeurIPS)Chenrui Cao, Liangcheng Song, Zenan Li, et al.2025 · 7 citations
25. Scaling up Multi-Turn Off-Policy RL and Multi-Agent Tree Search for LLM Step-ProversarXiv:2509.06493Ran Xin, Zeyu Zheng, Yanchen Nie, et al.2025 · 7 citations
26. StepFun-Formalizer: Unlocking the Autoformalization Potential of LLMs through Knowledge-Reasoning FusionarXiv:2508.04440Yutong Wu, Di Huang, Ruosi Wan, et al.2025 · 7 citations
27. Autoformalizer with Tool FeedbackarXiv:2510.06857Qi Guo; Jianing Wang; Jianfei Zhang; Deyang Kong; Xiangzhou Huang; Xiangyu Xi; Wei Wang; Jingang Wang; Xunliang Cai; Shikun Zhang;, Wei Ye2025 · 6 citations
28. ProofFlow: A Dependency Graph Approach to Faithful Proof AutoformalizationarXiv:2510.15981Rafael Cabral, Tuan Manh Do, Xuejun Yu, et al.2025 · 5 citations
29. ImProver: Agent-Based Automated Proof OptimizationarXiv:2410.04753Riyaz Ahuja, Jeremy Avigad, Prasad Tetali, et al.2024 · 5 citations
30. miniF2F-Lean Revisited: Reviewing Limitations and Charting a Path ForwardConference on Neural Information Processing Systems (NeurIPS)Azim Ospanov, Farzan Farnia, Roozbeh Yousefzadeh2025 · 4 citations
31. LLM-Powered Benchmark Factory: Reliable, Generic, and EfficientAnnual Meeting of the Association for Computational Linguistics (ACL)Peiwen Yuan, Shaoxiong Feng, Yiwei Li, et al.2026 · 3 citations
32. TabularMath: Understanding Math Reasoning over Tables with Large Language ModelsFindings of the Association for Computational LinguisticsShi-Yu Tian, Zhi Zhou, Wei Dong, et al.2026 · 3 citations
33. A Survey of Deep Learning for Geometry Problem SolvingAnnual Meeting of the Association for Computational Linguistics (ACL)Jianzhe Ma, Wenxuan Wang, Qin Jin2026 · 1 citation
34. FormalScience: Scalable Human-in-the-Loop Autoformalisation of Science with Agentic Code Generation in LeanAnnual Meeting of the Association for Computational Linguistics (ACL)Jordan Meadows, Lan Zhang, Andre Freitas2026
35. Language Models Learn Universal Representations of Numbers and Here's Why You Should CareAnnual Meeting of the Association for Computational Linguistics (ACL)Michal Štefánik, Timothee Mickus, Marek Kadlčík, et al.2026

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