---
title: "Who cites Charles Staats — 186 papers of our library"
description: "186 papers of the Elamur Research library cite the works of Charles Staats, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/charles-staats/cited-by/"
---
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# Who cites Charles Staats

204 citations of their works from 186 papers of our library (of the 149,439 whose bibliographies we read) · 92 with a page here, the most cited first · [← Charles Staats](https://md.research.elamur.ai/free/en/authors/charles-staats/)

1. **[A Survey on Evaluation of Large Language Models](https://md.research.elamur.ai/free/en/papers/chang-2023-survey-evaluation-large-language-models/) [ACM Transactions on Intelligent Systems and Technology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-intelligent-systems-and-technology/)**Yupeng Chang, Xu Wang, Jindong Wang, et al.*2023 · 3,648 citations*
2. **[A Survey of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/) [Frontiers of Computer Science](https://md.research.elamur.ai/free/en/venues/frontiers-of-computer-science/)**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,875 citations*
3. **[Solving Quantitative Reasoning Problems with Language Models](https://md.research.elamur.ai/free/en/papers/lewkowycz-2022-solving-quantitative-reasoning-problems-language/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Aitor Lewkowycz, Anders Andreassen, David Dohan, et al.*2022 · 992 citations*
4. [**Logic-LM: Empowering Large Language Models with Symbolic Solvers for Faithful Logical Reasoning arXiv:2305.12295**Liangming Pan, Alon Albalak, Xinyi Wang, et al.*2023 · 374 citations*](https://md.research.elamur.ai/free/en/papers/pan-2023-logic-lm-empowering-large-language/)
5. [**Augmented Language Models: a Survey arXiv:2302.07842**Grégoire Mialon, Roberto Dessì, Maria Lomeli, et al.*2023 · 369 citations*](https://md.research.elamur.ai/free/en/papers/mialon-2023-augmented-language-models-survey/)
6. [**Llemma: An Open Language Model For Mathematics arXiv:2310.10631**Zhangir Azerbayev, Hailey Schoelkopf, Keiran Paster, et al.*2023 · 286 citations*](https://md.research.elamur.ai/free/en/papers/azerbayev-2023-llemma-open-language-model-mathematics/)
7. **[LeanDojo: Theorem Proving with Retrieval-Augmented Language Models](https://md.research.elamur.ai/free/en/papers/yang-2023-leandojo-theorem-proving-retrieval-augmented/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Kaiyu Yang, Aidan M. Swope, Alex Gu, et al.*2023 · 253 citations*
8. **[Self-planning Code Generation with Large Language Models](https://md.research.elamur.ai/free/en/papers/jiang-2023-self-planning-code-generation-large/) [ACM Transactions on Software Engineering and Methodology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-software-engineering-and-methodology/)**Xue Jiang, Yihong Dong, Lecheng Wang, et al.*2023 · 223 citations*
9. **[Language Models of Code are Few-Shot Commonsense Learners](https://md.research.elamur.ai/free/en/papers/madaan-2022-language-models-code-few-shot/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Aman Madaan, Shuyan Zhou, Uri Alon, et al.*2022 · 212 citations*
10. **[A Survey of Safety and Trustworthiness of Large Language Models through the Lens of Verification and Validation](https://md.research.elamur.ai/free/en/papers/huang-2023-survey-safety-trustworthiness-large-language/) [Artificial Intelligence Review](https://md.research.elamur.ai/free/en/venues/artificial-intelligence-review/)**Xiaowei Huang, Wenjie Ruan, Wei Huang, et al.*2023 · 199 citations*
11. [**Draft, Sketch, and Prove: Guiding Formal Theorem Provers with Informal Proofs arXiv:2210.12283**Albert Q. Jiang, Sean Welleck, Jin Peng Zhou, et al.*2022 · 178 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2022-draft-sketch-prove-guiding-formal/)
12. **[Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2025-towards-reasoning-era-survey-long/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Libo Qin, Jinhao Liu, et al.*2025 · 176 citations*
13. [**Baldur: Whole-Proof Generation and Repair with Large Language Models arXiv:2303.04910**Emily First, Markus N. Rabe, Talia Ringer, et al.*2023 · 175 citations*](https://md.research.elamur.ai/free/en/papers/first-2023-baldur-whole-proof-generation-repair/)
14. **[LINC: A Neurosymbolic Approach for Logical Reasoning by Combining Language Models with First-Order Logic Provers](https://md.research.elamur.ai/free/en/papers/olausson-2023-linc-neurosymbolic-approach-logical-reasoning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Theo X. Olausson, Alex Gu, Benjamin Lipkin, et al.*2023 · 172 citations*
15. [**Reasoning with Language Model Prompting: A Survey arXiv:2212.09597**Shuofei Qiao, Yixin Ou, Ningyu Zhang, et al.*2022 · 161 citations*](https://md.research.elamur.ai/free/en/papers/qiao-2022-reasoning-language-model-prompting-survey/)
16. [**ProofNet: Autoformalizing and Formally Proving Undergraduate-Level Mathematics arXiv:2302.12433**Zhangir Azerbayev, Bartosz Piotrowski, Hailey Schoelkopf, et al.*2023 · 142 citations*](https://md.research.elamur.ai/free/en/papers/azerbayev-2023-proofnet-autoformalizing-formally-proving-undergraduate/)
17. [**Progressive-Hint Prompting Improves Reasoning in Large Language Models arXiv:2304.09797**Chuanyang Zheng, Zhengying Liu, Enze Xie, et al.*2023 · 131 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2023-progressive-hint-prompting-improves-reasoning/)
18. [**DeepSeek-Prover: Advancing Theorem Proving in LLMs through Large-Scale Synthetic Data arXiv:2405.14333**Huajian Xin, Daya Guo, Zhihong Shao, et al.*2024 · 111 citations*](https://md.research.elamur.ai/free/en/papers/xin-2024-deepseek-prover-advancing-theorem-proving/)
19. [**Text and Patterns: For Effective Chain of Thought, It Takes Two to Tango arXiv:2209.07686**Aman Madaan, Amir Yazdanbakhsh*2022 · 98 citations*](https://md.research.elamur.ai/free/en/papers/madaan-2022-text-patterns-effective-chain-thought/)
20. [**Teaching Algorithmic Reasoning via In-context Learning arXiv:2211.09066**Hattie Zhou, Azade Nova, Hugo Larochelle, et al.*2022 · 96 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2022-teaching-algorithmic-reasoning-context-learning/)
21. [**How well do Large Language Models perform in Arithmetic tasks? arXiv:2304.02015**Zheng Yuan, Hongyi Yuan, Chuanqi Tan, et al.*2023 · 93 citations*](https://md.research.elamur.ai/free/en/papers/yuan-2023-well-large-language-models-perform/)
22. [**Foundational Challenges in Assuring Alignment and Safety of Large Language Models arXiv:2404.09932**Usman Anwar, Abulhair Saparov, Javier Rando, et al.*2024 · 87 citations*](https://md.research.elamur.ai/free/en/papers/anwar-2024-foundational-challenges-assuring-alignment-safety/)
23. **[Mathematics, word problems, common sense, and artificial intelligence](https://md.research.elamur.ai/free/en/papers/davis-2023-mathematics-word-problems-common-sense/) [Bulletin of the American Mathematical Society](https://md.research.elamur.ai/free/en/venues/bulletin-of-the-american-mathematical-society/)**Ernest Davis*2023 · 86 citations*
24. [**Goedel-Prover: A Frontier Model for Open-Source Automated Theorem Proving arXiv:2502.07640**Yong Lin, Shange Tang, Bohan Lyu, et al.*2025 · 84 citations*](https://md.research.elamur.ai/free/en/papers/lin-2025-goedel-prover-frontier-model-open/)
25. **[DOC: Improving Long Story Coherence With Detailed Outline Control](https://md.research.elamur.ai/free/en/papers/yang-2023-doc-improving-long-story-coherence/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kevin Yang, Dan Klein, Nanyun Peng, et al.*2023 · 83 citations*
26. **[Lean Workbook: A large-scale Lean problem set formalized from natural language math problems](https://md.research.elamur.ai/free/en/papers/ying-2024-lean-workbook-large-scale-lean/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Huaiyuan Ying, Zijian Wu, Yihan Geng, et al.*2024 · 80 citations*
27. [**LEGO-Prover: Neural Theorem Proving with Growing Libraries arXiv:2310.00656**Haiming Wang, Huajian Xin, Chuanyang Zheng, et al.*2023 · 79 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-lego-prover-neural-theorem-proving/)
28. [**FIMO: A Challenge Formal Dataset for Automated Theorem Proving arXiv:2309.04295**Chengwu Liu, Jianhao Shen, Huajian Xin, et al.*2023 · 53 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-fimo-challenge-formal-dataset-automated/)
29. **[Verification and Refinement of Natural Language Explanations through LLM-Symbolic Theorem Proving](https://md.research.elamur.ai/free/en/papers/quan-2024-verification-refinement-natural-language-explanations/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xin Quan, Marco Valentino, Louise A. Dennis, et al.*2024 · 52 citations*
30. [**Lean-STaR: Learning to Interleave Thinking and Proving arXiv:2407.10040**Haohan Lin, Zhiqing Sun, Sean Welleck, et al.*2024 · 51 citations*](https://md.research.elamur.ai/free/en/papers/lin-2024-lean-star-learning-interleave-thinking/)
31. **[TheoremLlama: Transforming General-Purpose LLMs into Lean4 Experts](https://md.research.elamur.ai/free/en/papers/wang-2024-theoremllama-transforming-general-purpose-llms/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ruida Wang, Jipeng Zhang, Yizhen Jia, et al.*2024 · 51 citations*
32. **[BFS-Prover: Scalable Best-First Tree Search for LLM-based Automatic Theorem Proving](https://md.research.elamur.ai/free/en/papers/xin-2025-bfs-prover-scalable-best-first/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ran Xin, Chenguang Xi, Jie Yang, et al.*2025 · 49 citations*
33. [**Formal Mathematical Reasoning: A New Frontier in AI arXiv:2412.16075**Kaiyu Yang, Gabriel Poesia, Jingxuan He, et al.*2024 · 49 citations*](https://md.research.elamur.ai/free/en/papers/yang-2024-formal-mathematical-reasoning-new-frontier/)
34. [**A Survey on Deep Learning for Theorem Proving arXiv:2404.09939**Zhaoyu Li, Jialiang Sun, Logan Murphy, et al.*2024 · 46 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-survey-deep-learning-theorem-proving/)
35. [**Towards AI-Assisted Synthesis of Verified Dafny Methods arXiv:2402.00247**Md Rakib Hossain Misu, Cristina V. Lopes, Iris Ma, et al.*2024 · 46 citations*](https://md.research.elamur.ai/free/en/papers/misu-2024-ai-assisted-synthesis-verified-dafny/)
36. [**Don't Trust: Verify — Grounding LLM Quantitative Reasoning with Autoformalization arXiv:2403.18120**Jin Peng Zhou, Charles Staats, Wenda Li, et al.*2024 · 45 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2024-don-t-trust-verify-grounding/)
37. [**Evaluating Language Models for Mathematics through Interactions arXiv:2306.01694**Katherine M. Collins, Albert Q. Jiang, Simon Frieder, et al.*2023 · 40 citations*](https://md.research.elamur.ai/free/en/papers/collins-2023-evaluating-language-models-mathematics-through/)
38. [**A Survey of Frontiers in LLM Reasoning: Inference Scaling, Learning to Reason, and Agentic Systems arXiv:2504.09037**Zixuan Ke, Fangkai Jiao, Yifei Ming, et al.*2025 · 39 citations*](https://md.research.elamur.ai/free/en/papers/ke-2025-survey-frontiers-llm-reasoning-inference/)
39. [**Lean Copilot: Large Language Models as Copilots for Theorem Proving in Lean arXiv:2404.12534**Peiyang Song, Kaiyu Yang, Anima Anandkumar*2024 · 39 citations*](https://md.research.elamur.ai/free/en/papers/song-2024-lean-copilot-large-language-models/)
40. [**Multilingual Mathematical Autoformalization arXiv:2311.03755**Albert Q. Jiang, Wenda Li, Mateja Jamnik*2023 · 37 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2023-multilingual-mathematical-autoformalization/)
41. [**Magnushammer: A Transformer-Based Approach to Premise Selection arXiv:2303.04488**Maciej Mikuła, Szymon Tworkowski, Szymon Antoniak, et al.*2023 · 35 citations*](https://md.research.elamur.ai/free/en/papers/mikula-2023-magnushammer-transformer-based-approach-premise/)
42. [**Herald: A Natural Language Annotated Lean 4 Dataset arXiv:2410.10878**Guoxiong Gao, Yutong Wang, Jiedong Jiang, et al.*2024 · 33 citations*](https://md.research.elamur.ai/free/en/papers/gao-2024-herald-natural-language-annotated-lean/)
43. [**Process-Driven Autoformalization in Lean 4 arXiv:2406.01940**Jianqiao Lu, Yingjia Wan, Zhengying Liu, et al.*2024 · 33 citations*](https://md.research.elamur.ai/free/en/papers/lu-2024-process-driven-autoformalization-lean-4/)
44. [**FormalMATH: Benchmarking Formal Mathematical Reasoning of Large Language Models arXiv:2505.02735**Zhouliang Yu, Ruotian Peng, Keyi Ding, et al.*2025 · 31 citations*](https://md.research.elamur.ai/free/en/papers/yu-2025-formalmath-benchmarking-formal-mathematical-reasoning/)
45. [**Gold-medalist Performance in Solving Olympiad Geometry with AlphaGeometry2 arXiv:2502.03544**Yuri Chervonyi, Trieu H. Trinh, Miroslav Olšák, et al.*2025 · 31 citations*](https://md.research.elamur.ai/free/en/papers/chervonyi-2025-gold-medalist-performance-solving-olympiad/)
46. **[Aristotle: IMO-level Automated Theorem Proving](https://md.research.elamur.ai/free/en/papers/achim-2025-aristotle-imo-level-automated-theorem/) [SuperIntelligence - Robotics - Safety & Alignment](https://md.research.elamur.ai/free/en/venues/superintelligence-robotics-safety-alignment/)**Tudor Achim, Alex Best, Alberto Bietti, et al.*2025 · 29 citations*
47. [**MUSTARD: Mastering Uniform Synthesis of Theorem and Proof Data arXiv:2402.08957 (ICLR 2024 spotlight)**Yinya Huang, Xiaohan Lin, Zhengying Liu, et al.*2024 · 29 citations*](https://md.research.elamur.ai/free/en/papers/huang-2024-mustard-mastering-uniform-synthesis-theorem/)
48. [**Transformers Can Achieve Length Generalization But Not Robustly arXiv:2402.09371**Yongchao Zhou, Uri Alon, Xinyun Chen, et al.*2024 · 29 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2024-transformers-achieve-length-generalization-but/)
49. [**Decomposing the Enigma: Subgoal-based Demonstration Learning for Formal Theorem Proving arXiv:2305.16366**Xueliang Zhao, Wenda Li, Lingpeng Kong*2023 · 29 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2023-decomposing-enigma-subgoal-based-demonstration/)
50. [**Lyra: Orchestrating Dual Correction in Automated Theorem Proving arXiv:2309.15806**Chuanyang Zheng, Haiming Wang, Enze Xie, et al.*2023 · 24 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2023-lyra-orchestrating-dual-correction-automated/)
51. [**Autoformalizing Euclidean Geometry arXiv:2405.17216**Logan Murphy, Kaiyu Yang, Jialiang Sun, et al.*2024 · 23 citations*](https://md.research.elamur.ai/free/en/papers/murphy-2024-autoformalizing-euclidean-geometry/)
52. [**LEAN-GitHub: Compiling GitHub LEAN repositories for a versatile LEAN prover arXiv:2407.17227**Zijian Wu, Jiayu Wang, Dahua Lin, et al.*2024 · 23 citations*](https://md.research.elamur.ai/free/en/papers/wu-2024-lean-github-compiling-github-lean/)
53. [**Certified Deductive Reasoning with Language Models arXiv:2306.04031**Gabriel Poesia, Kanishk Gandhi, Eric Zelikman, et al.*2023 · 23 citations*](https://md.research.elamur.ai/free/en/papers/poesia-2023-certified-deductive-reasoning-language-models/)
54. **[TRIGO: Benchmarking Formal Mathematical Proof Reduction for Generative Language Models](https://md.research.elamur.ai/free/en/papers/xiong-2023-trigo-benchmarking-formal-mathematical-proof/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jing Xiong, Jianhao Shen, Ye Yuan, et al.*2023 · 21 citations*
55. [**Seed-Prover 1.5: Mastering Undergraduate-Level Theorem Proving via Learning from Experience arXiv:2512.17260**Jiangjie Chen, Wenxiang Chen, Jiacheng Du, et al.*2025 · 19 citations*](https://md.research.elamur.ai/free/en/papers/chen-2025-seed-prover-1-5/)
56. **[Autoformalize Mathematical Statements by Symbolic Equivalence and Semantic Consistency](https://md.research.elamur.ai/free/en/papers/li-2024-autoformalize-mathematical-statements-symbolic-equivalence/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zenan Li, Yifan Wu, Zhaoyu Li, et al.*2024 · 19 citations*
57. **[Proving Theorems Recursively](https://md.research.elamur.ai/free/en/papers/wang-2024-proving-theorems-recursively/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Haiming Wang, Huajian Xin, Zhengying Liu, et al.*2024 · 19 citations*
58. [**Towards a Mathematics Formalisation Assistant using Large Language Models arXiv:2211.07524**Ayush Agrawal, Siddhartha Gadgil, Navin Goyal, et al.*2022 · 19 citations*](https://md.research.elamur.ai/free/en/papers/agrawal-2022-mathematics-formalisation-assistant-large-language/)
59. [**FormalAlign: Automated Alignment Evaluation for Autoformalization arXiv:2410.10135**Jianqiao Lu, Yingjia Wan, Yinya Huang, et al.*2024 · 18 citations*](https://md.research.elamur.ai/free/en/papers/lu-2024-formalalign-automated-alignment-evaluation-autoformalization/)
60. **[Safe: Enhancing Mathematical Reasoning in Large Language Models via Retrospective Step-aware Formal Verification](https://md.research.elamur.ai/free/en/papers/liu-2025-safe-enhancing-mathematical-reasoning-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chengwu Liu, Ye Yuan, Yichun Yin, et al.*2025 · 17 citations*
61. **[ATLAS: Autoformalizing Theorems through Lifting, Augmentation, and Synthesis of Data](https://md.research.elamur.ai/free/en/papers/liu-2025-atlas-autoformalizing-theorems-through-lifting/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Xiaoyang Liu, Kangjie Bao, Jiashuo Zhang, et al.*2025 · 16 citations*
62. [**Solving Formal Math Problems by Decomposition and Iterative Reflection arXiv:2507.15225**Yichi Zhou, Jianqiu Zhao, Yongxin Zhang, et al.*2025 · 16 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2025-solving-formal-math-problems-decomposition/)
63. **[Neuro-Symbolic Data Generation for Math Reasoning](https://md.research.elamur.ai/free/en/papers/li-2024-neuro-symbolic-data-generation-math/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zenan Li, Zhi Zhou, Yuan Yao, et al.*2024 · 14 citations*
64. **[CriticLean: Critic-Guided Reinforcement Learning for Mathematical Formalization](https://md.research.elamur.ai/free/en/papers/peng-2026-criticlean-critic-guided-reinforcement-learning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhongyuan Peng, Yifan Yao, Kaijing Ma, et al.*2026 · 12 citations*
65. [**Autoformalization in the Era of Large Language Models: A Survey arXiv:2505.23486**Ke Weng, Lun Du, Sirui Li, et al.*2025 · 11 citations*](https://md.research.elamur.ai/free/en/papers/weng-2025-autoformalization-era-large-language-models/)
66. **[Autoformalization in the Wild: Assessing LLMs on Real-World Mathematical Definitions](https://md.research.elamur.ai/free/en/papers/zhang-2025-autoformalization-wild-assessing-llms-real/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Lan Zhang, Marco Valentino, Andre Freitas*2025 · 11 citations*
67. **[Consistent Autoformalization for Constructing Mathematical Libraries](https://md.research.elamur.ai/free/en/papers/zhang-2024-consistent-autoformalization-constructing-mathematical-libraries/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Lan Zhang, Xin Quan, Andre Freitas*2024 · 11 citations*
68. [**SubgoalXL: Subgoal-based Expert Learning for Theorem Proving arXiv:2408.11172**Xueliang Zhao, Lin Zheng, Haige Bo, et al.*2024 · 10 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2024-subgoalxl-subgoal-based-expert-learning/)
69. [**Mathesis: Towards Formal Theorem Proving from Natural Languages arXiv:2506.07047**Yu Xuejun, Jianyuan Zhong, Zijin Feng, et al.*2025 · 9 citations*](https://md.research.elamur.ai/free/en/papers/xuejun-2025-mathesis-towards-formal-theorem-proving/)
70. **[Theorem Prover as a Judge for Synthetic Data Generation](https://md.research.elamur.ai/free/en/papers/leang-2025-theorem-prover-as-judge-synthetic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Joshua Ong Jun Leang, Giwon Hong, Wenda Li, et al.*2025 · 9 citations*
71. [**ReForm: Reflective Autoformalization with Prospective Bounded Sequence Optimization arXiv:2510.24592**Guoxin Chen, Jing Wu, Xinjie Chen, et al.*2025 · 8 citations*](https://md.research.elamur.ai/free/en/papers/chen-2025-reform-reflective-autoformalization-prospective-bounded/)
72. [**A Survey on Feedback-based Multi-step Reasoning for Large Language Models on Mathematics arXiv:2502.14333**Ting-Ruen Wei, Haowei Liu, Xuyang Wu, et al.*2025 · 7 citations*](https://md.research.elamur.ai/free/en/papers/wei-2025-survey-feedback-based-multi-step/)
73. **[Let's Reason Formally: Natural-Formal Hybrid Reasoning Enhances LLM's Math Capability](https://md.research.elamur.ai/free/en/papers/wang-2025-let-s-reason-formally-natural/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ruida Wang, Yuxin Li, Yi R. Fung, et al.*2025 · 7 citations*
74. **[Reviving DSP for Advanced Theorem Proving in the Era of Reasoning Models](https://md.research.elamur.ai/free/en/papers/cao-2025-reviving-dsp-advanced-theorem-proving/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Chenrui Cao, Liangcheng Song, Zenan Li, et al.*2025 · 7 citations*
75. [**StepFun-Formalizer: Unlocking the Autoformalization Potential of LLMs through Knowledge-Reasoning Fusion arXiv:2508.04440**Yutong Wu, Di Huang, Ruosi Wan, et al.*2025 · 7 citations*](https://md.research.elamur.ai/free/en/papers/wu-2025-stepfun-formalizer-unlocking-autoformalization/)
76. [**A New Approach Towards Autoformalization arXiv:2310.07957**Nilay Patel, Rahul Saha, Jeffrey Flanigan*2023 · 7 citations*](https://md.research.elamur.ai/free/en/papers/patel-2023-new-approach-towards-autoformalization/)
77. [**Autoformalizer with Tool Feedback arXiv:2510.06857**Qi Guo; Jianing Wang; Jianfei Zhang; Deyang Kong; Xiangzhou Huang; Xiangyu Xi; Wei Wang; Jingang Wang; Xunliang Cai; Shikun Zhang;, Wei Ye*2025 · 6 citations*](https://md.research.elamur.ai/free/en/papers/guo-2025-autoformalizer-tool-feedback/)
78. [**ProofFlow: A Dependency Graph Approach to Faithful Proof Autoformalization arXiv:2510.15981**Rafael Cabral, Tuan Manh Do, Xuejun Yu, et al.*2025 · 5 citations*](https://md.research.elamur.ai/free/en/papers/cabral-2025-proofflow-dependency-graph-approach-faithful/)
79. [**GFLean: An Autoformalisation Framework for Lean via GF arXiv:2404.01234**Shashank Pathak*2024 · 5 citations*](https://md.research.elamur.ai/free/en/papers/pathak-2024-gflean-autoformalisation-framework-lean-gf/)
80. **[miniF2F-Lean Revisited: Reviewing Limitations and Charting a Path Forward](https://md.research.elamur.ai/free/en/papers/ospanov-2025-minif2f-lean-revisited-reviewing-limitations/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Azim Ospanov, Farzan Farnia, Roozbeh Yousefzadeh*2025 · 4 citations*
81. **[Graders Should Cheat: Privileged Information Enables Expert-Level Automated Evaluations](https://md.research.elamur.ai/free/en/papers/zhou-2025-graders-should-cheat-privileged-information/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jin Peng Zhou, Séb Arnold, Nan Ding, et al.*2025 · 3 citations*
82. **[Adaptive LLM-Symbolic Reasoning via Dynamic Logical Solver Composition](https://md.research.elamur.ai/free/en/papers/xu-2026-adaptive-llm-symbolic-reasoning-dynamic/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Lei Xu, Pierre Beckmann, Marco Valentino, et al.*2026 · 2 citations*
83. **[Argument-Based Consistency in Toxicity Explanations of LLMs](https://md.research.elamur.ai/free/en/papers/mothilal-2026-argument-based-consistency-toxicity-explanations/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ramaravind Kommiya Mothilal, Joanna Roy, Syed Ishtiaque Ahmed, et al.*2026 · 2 citations*
84. **[GIL-Zaragoza at SemEval 2026 Task 11: Comparing Classification, Autoformalization, and Ontologies for Formal Reasoning Capabilities](https://md.research.elamur.ai/free/en/papers/ponce-2026-gil-zaragoza-semeval-2026-task/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Francisco Lopez-Ponce, Lucia Pitarch, Iván Saavedra Martínez, et al.*2026 · 1 citation*
85. **[ReProbe: Efficient Test-Time Scaling of Multi-Step Reasoning by Probing Internal States of Large Language Models](https://md.research.elamur.ai/free/en/papers/ni-2026-reprobe-efficient-test-time-scaling/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jingwei Ni, Ekaterina Fadeeva, Tianyi Wu, et al.*2026 · 1 citation*
86. **[Solve-Detect-Verify: Inference-Time Scaling with Flexible Generative Verifier](https://md.research.elamur.ai/free/en/papers/zhong-2026-solve-detect-verify-inference-time/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jianyuan Zhong, Zeju Li, Zhijian Xu, et al.*2026 · 1 citation*
87. **[Beyond Memorization: Testing LLM Reasoning on Unseen Theory of Computation Tasks](https://md.research.elamur.ai/free/en/papers/shelat-2026-beyond-memorization-testing-llm-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shlok Shelat, Jay Raval, Souvik Roy, et al.*2026*
88. **[CARL: Constraint-Aware Reinforcement Learning for Planning with LLMs](https://md.research.elamur.ai/free/en/papers/qi-2026-carl-constraint-aware-reinforcement-learning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qiuyi Qi, Jinjian Zhang, Mutian Bao, et al.*2026*
89. **[FormalScience: Scalable Human-in-the-Loop Autoformalisation of Science with Agentic Code Generation in Lean](https://md.research.elamur.ai/free/en/papers/meadows-2026-formalscience-scalable-human-loop-autoformalisation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jordan Meadows, Lan Zhang, Andre Freitas*2026*
90. **[Format-Adapter: Improving Reasoning Capability of LLMs by Adapting Suitable Format](https://md.research.elamur.ai/free/en/papers/wang-2026-format-adapter-improving-reasoning-capability/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Dingzirui Wang, Xuanliang Zhang, Rongyu Cao, et al.*2026*
91. **[From Natural Language to Certified Geometry Proofs: A Survey of LLM-Augmented Verification and Neuro-Symbolic Theorem Proving](https://md.research.elamur.ai/free/en/papers/tzachristas-2026-natural-language-certified-geometry-proofs/) [Big Picture v2: Crafting a Research Narrative](https://md.research.elamur.ai/free/en/venues/bigpicture/)**Ioannis Tzachristas, Georgios Tzachristas*2026*
92. **[STCOR: A Trilevel Syllogism-Driven Reasoning Framework](https://md.research.elamur.ai/free/en/papers/yang-2026-stcor-trilevel-syllogism-driven-reasoning/) [Workshop on Argument Mining](https://md.research.elamur.ai/free/en/venues/argmining/)**Keying Yang, Hao Wang, Chengtao Jian, et al.*2026*

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