---
title: "Who cites Bartosz Piotrowski — 152 papers of our library"
description: "152 papers of the Elamur Research library cite the works of Bartosz Piotrowski, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/bartosz-piotrowski/cited-by/"
---
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# Who cites Bartosz Piotrowski

172 citations of their works from 152 papers of our library (of the 149,439 whose bibliographies we read) · 78 with a page here, the most cited first · [← Bartosz Piotrowski](https://md.research.elamur.ai/free/en/authors/bartosz-piotrowski/)

1. **[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*
2. [**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/)
3. **[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*
4. **[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*
5. [**Omni-MATH: A Universal Olympiad Level Mathematic Benchmark For Large Language Models arXiv:2410.07985**Bofei Gao, Feifan Song, Zhe Yang, et al.*2024 · 163 citations*](https://md.research.elamur.ai/free/en/papers/gao-2024-omni-math-universal-olympiad-level/)
6. [**OpenWebMath: An Open Dataset of High-Quality Mathematical Web Text arXiv:2310.06786**Keiran Paster, Marco Dos Santos, Zhangir Azerbayev, et al.*2023 · 132 citations*](https://md.research.elamur.ai/free/en/papers/paster-2023-openwebmath-open-dataset-high-quality/)
7. [**DeepSeek-Prover-V2: Advancing Formal Mathematical Reasoning via Reinforcement Learning for Subgoal Decomposition arXiv:2504.21801**Z. Z. Ren, Zhihong Shao, Junxiao Song, et al.*2025 · 122 citations*](https://md.research.elamur.ai/free/en/papers/ren-2025-deepseek-prover-v2-advancing-formal/)
8. [**DeepSeek-Prover-V1.5: Harnessing Proof Assistant Feedback for Reinforcement Learning and Monte-Carlo Tree Search arXiv:2408.08152**Huajian Xin, Z. Z. Ren, Junxiao Song, et al.*2024 · 116 citations*](https://md.research.elamur.ai/free/en/papers/xin-2024-deepseek-prover-v1-5-harnessing/)
9. **[PutnamBench: Evaluating Neural Theorem-Provers on the Putnam Mathematical Competition](https://md.research.elamur.ai/free/en/papers/tsoukalas-2024-putnambench-evaluating-neural-theorem-provers/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**George Tsoukalas, Jasper Lee, John Jennings, et al.*2024 · 93 citations*
10. [**Kimina-Prover Preview: Towards Large Formal Reasoning Models with Reinforcement Learning arXiv:2504.11354**Haiming Wang, Mert Unsal, Xiaohan Lin, et al.*2025 · 92 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-kimina-prover-preview-large-formal/)
11. [**InternLM-Math: Open Math Large Language Models Toward Verifiable Reasoning arXiv:2402.06332**Huaiyuan Ying, Shuo Zhang, Linyang Li, et al.*2024 · 90 citations*](https://md.research.elamur.ai/free/en/papers/ying-2024-internlm-math-open-math-large/)
12. [**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/)
13. **[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*
14. [**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/)
15. [**Reasoning Models Can Be Effective Without Thinking arXiv:2504.09858**Wenjie Ma, Jingxuan He, Charlie Snell, et al.*2025 · 58 citations*](https://md.research.elamur.ai/free/en/papers/ma-2025-reasoning-models-effective-thinking/)
16. [**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/)
17. **[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*
18. [**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/)
19. **[MathPile: A Billion-Token-Scale Pretraining Corpus for Math](https://md.research.elamur.ai/free/en/papers/wang-2023-mathpile-billion-token-scale-pretraining/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zengzhi Wang, Xuefeng Li, Rui Xia, et al.*2023 · 49 citations*
20. [**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/)
21. **[MathOdyssey: Benchmarking Mathematical Problem-Solving Skills in Large Language Models Using Odyssey Math Data](https://md.research.elamur.ai/free/en/papers/fang-2024-mathodyssey-benchmarking-mathematical-problem-solving/) [Scientific Data](https://md.research.elamur.ai/free/en/venues/scientific-data/)**Meng Fang, Xiangpeng Wan, Fei Lu, et al.*2024 · 46 citations*
22. [**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/)
23. [**STP: Self-play LLM Theorem Provers with Iterative Conjecturing and Proving arXiv:2502.00212**Kefan Dong, Tengyu Ma*2025 · 43 citations*](https://md.research.elamur.ai/free/en/papers/dong-2025-stp-self-play-llm-theorem/)
24. [**IsarStep: a Benchmark for High-level Mathematical Reasoning arXiv:2006.09265**Wenda Li, Lei Yu, Yuhuai Wu, et al.*2020 · 43 citations*](https://md.research.elamur.ai/free/en/papers/li-2020-isarstep-benchmark-high-level-mathematical/)
25. [**INT: An Inequality Benchmark for Evaluating Generalization in Theorem Proving arXiv:2007.02924**Yuhuai Wu, Albert Qiaochu Jiang, Jimmy Ba, et al.*2020 · 41 citations*](https://md.research.elamur.ai/free/en/papers/wu-2020-int-inequality-benchmark-evaluating-generalization/)
26. [**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/)
27. **[First Neural Conjecturing Datasets and Experiments](https://md.research.elamur.ai/free/en/papers/urban-2020-first-neural-conjecturing-datasets-experiments/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Josef Urban, Jan Jakubův*2020 · 40 citations*
28. [**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/)
29. [**LIME: Learning Inductive Bias for Primitives of Mathematical Reasoning arXiv:2101.06223**Yuhuai Wu, Markus Rabe, Wenda Li, et al.*2021 · 39 citations*](https://md.research.elamur.ai/free/en/papers/wu-2021-lime-learning-inductive-bias-primitives/)
30. [**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/)
31. [**Functional Benchmarks for Robust Evaluation of Reasoning Performance, and the Reasoning Gap arXiv:2402.19450**Saurabh Srivastava, Annarose M B, Anto P, et al.*2024 · 35 citations*](https://md.research.elamur.ai/free/en/papers/srivastava-2024-functional-benchmarks-robust-evaluation-reasoning/)
32. [**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/)
33. [**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/)
34. [**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/)
35. [**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/)
36. **[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*
37. [**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/)
38. **[Challenging the Boundaries of Reasoning: An Olympiad-Level Math Benchmark for Large Language Models](https://md.research.elamur.ai/free/en/papers/sun-2026-challenging-boundaries-reasoning-olympiad-level/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haoxiang Sun, Yingqian Min, Zhipeng Chen, et al.*2026 · 25 citations*
39. [**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/)
40. [**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/)
41. [**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/)
42. **[Towards Finding Longer Proofs](https://md.research.elamur.ai/free/en/papers/zombori-2019-finding-longer-proofs/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Zsolt Zombori, Adrián Csiszárik, Henryk Michalewski, et al.*2019 · 21 citations*
43. [**CombiBench: Benchmarking LLM Capability for Combinatorial Mathematics arXiv:2505.03171**Junqi Liu, Xiaohan Lin, Jonas Bayer, et al.*2025 · 20 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-combibench-benchmarking-llm-capability-combinatorial/)
44. **[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*
45. [**Graph2Tac: Online Representation Learning of Formal Math Concepts arXiv:2401.02949**Lasse Blaauwbroek, Miroslav Olšák, Jason Rute, et al.*2024 · 19 citations*](https://md.research.elamur.ai/free/en/papers/blaauwbroek-2024-graph2tac-online-representation-learning-formal/)
46. **[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*
47. [**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/)
48. [**miniCTX: Neural Theorem Proving with (Long-)Contexts arXiv:2408.03350**Jiewen Hu, Thomas Zhu, Sean Welleck*2024 · 18 citations*](https://md.research.elamur.ai/free/en/papers/hu-2024-minictx-neural-theorem-proving-long/)
49. **[APOLLO: Automated LLM and Lean Collaboration for Advanced Formal Reasoning](https://md.research.elamur.ai/free/en/papers/ospanov-2025-apollo-automated-llm-lean-collaboration/) [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 · 17 citations*
50. **[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*
51. [**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/)
52. [**Prover Agent: An Agent-Based Framework for Formal Mathematical Proofs arXiv:2506.19923**Kaito Baba, Chaoran Liu, Shuhei Kurita, et al.*2025 · 14 citations*](https://md.research.elamur.ai/free/en/papers/baba-2025-prover-agent-agent-based-framework/)
53. [**U-MATH: A University-Level Benchmark for Evaluating Mathematical Skills in LLMs arXiv:2412.03205**Konstantin Chernyshev, Vitaliy Polshkov, Ekaterina Artemova, et al.*2024 · 13 citations*](https://md.research.elamur.ai/free/en/papers/chernyshev-2024-u-math-university-level-benchmark/)
54. **[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*
55. [**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/)
56. **[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*
57. **[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*
58. [**MIND: Math Informed syNthetic Dialogues for Pretraining LLMs arXiv:2410.12881**Syeda Nahida Akter, Shrimai Prabhumoye, John Kamalu, et al.*2024 · 11 citations*](https://md.research.elamur.ai/free/en/papers/akter-2024-mind-math-informed-synthetic-dialogues/)
59. [**REAL-Prover: Retrieval Augmented Lean Prover for Mathematical Reasoning arXiv:2505.20613**Ziju Shen, Naohao Huang, Fanyi Yang, et al.*2025 · 10 citations*](https://md.research.elamur.ai/free/en/papers/shen-2025-real-prover-retrieval-augmented-lean/)
60. [**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/)
61. **[Examining False Positives under Inference Scaling for Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/wang-2025-examining-false-positives-under-inference/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yu Wang, Nan Yang, Liang Wang, et al.*2025 · 9 citations*
62. [**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/)
63. [**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/)
64. [**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/)
65. **[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*
66. **[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*
67. [**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/)
68. [**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/)
69. **[Mathematical Proof as a Litmus Test: Revealing Failure Modes of Advanced Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/guo-2026-mathematical-proof-as-litmus-test/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Dadi Guo, Jiayu Liu, Zhiyuan Fan, et al.*2026 · 5 citations*
70. **[MASA: LLM-Driven Multi-Agent Systems for Autoformalization](https://md.research.elamur.ai/free/en/papers/zhang-2025-masa-llm-driven-multi-agent/) [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 · 5 citations*
71. [**Premise Selection for a Lean Hammer arXiv:2506.07477**Thomas Zhu, Joshua Clune, Jeremy Avigad, et al.*2025 · 5 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2025-premise-selection-lean-hammer/)
72. **[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*
73. **[MPS-Prover: Advancing Stepwise Theorem Proving by Multi-Perspective Search and Data Curation](https://md.research.elamur.ai/free/en/papers/liang-2025-mps-prover-advancing-stepwise-theorem/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zhenwen Liang, Linfeng Song, Yang Li, et al.*2025 · 4 citations*
74. **[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*
75. **[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*
76. **[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*
77. **[Open Problems Solved by LLMs? A Survey of Verifiable Mathematical Discovery](https://md.research.elamur.ai/free/en/papers/tzachristas-2026-open-problems-solved-llms-survey/) [Big Picture v2: Crafting a Research Narrative](https://md.research.elamur.ai/free/en/venues/bigpicture/)**Ioannis Tzachristas, Georgios Tzachristas, Aifen Sui*2026*
78. **[Reliable Use of Lemmas via Eligibility Reasoning and Section-Aware Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/xu-2026-reliable-use-lemmas-eligibility-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhikun Xu, Xiaodong Yu, Ben Zhou, et al.*2026*

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