---
title: "Who cites Piotr Miłoś — 113 papers of our library"
description: "113 papers of the Elamur Research library cite the works of Piotr Miłoś, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/piotr-milos/cited-by/"
---
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# Who cites Piotr Miłoś

130 citations of their works from 113 papers of our library (of the 149,439 whose bibliographies we read) · 45 with a page here, the most cited first · [← Piotr Miłoś](https://md.research.elamur.ai/free/en/authors/piotr-milos/)

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. **[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*
3. [**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/)
4. **[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*
5. [**Autoformalization with Large Language Models arXiv:2205.12615**Yuhuai Wu, Albert Q. Jiang, Wenda Li, et al.*2022 · 204 citations*](https://md.research.elamur.ai/free/en/papers/wu-2022-autoformalization-large-language-models/)
6. [**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/)
7. [**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/)
8. [**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/)
9. [**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/)
10. [**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/)
11. [**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/)
12. [**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/)
13. **[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*
14. [**Foundation Models for Decision Making: Problems, Methods, and Opportunities arXiv:2303.04129**Sherry Yang, Ofir Nachum, Yilun Du, et al.*2023 · 92 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-foundation-models-decision-making-problems/)
15. [**Deep Reinforcement Learning at the Edge of the Statistical Precipice arXiv:2108.13264**Rishabh Agarwal, Max Schwarzer, Pablo Samuel Castro, et al.*2021 · 90 citations*](https://md.research.elamur.ai/free/en/papers/agarwal-2021-deep-reinforcement-learning-edge-statistical/)
16. [**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/)
17. **[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*
18. [**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/)
19. [**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/)
20. **[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*
21. [**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/)
22. [**An In-Context Learning Agent for Formal Theorem-Proving arXiv:2310.04353**Amitayush Thakur, George Tsoukalas, Yeming Wen, et al.*2023 · 47 citations*](https://md.research.elamur.ai/free/en/papers/thakur-2023-context-learning-agent-formal-theorem/)
23. [**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/)
24. [**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/)
25. **[DT-Solver: Automated Theorem Proving with Dynamic-Tree Sampling Guided by Proof-level Value Function](https://md.research.elamur.ai/free/en/papers/wang-2023-dt-solver-automated-theorem-proving/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haiming Wang, Ye Yuan, Zhengying Liu, et al.*2023 · 40 citations*
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. [**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/)
28. [**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/)
29. [**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/)
30. **[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*
31. [**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/)
32. **[AutoVerus: Automated Proof Generation for Rust Code](https://md.research.elamur.ai/free/en/papers/yang-2024-autoverus-automated-proof-generation-rust/) [Proceedings of the ACM on Programming Languages](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-acm-on-programming-languages/)**Chenyuan Yang, Xuheng Li, Md Rakib Hossain Misu, et al.*2024 · 28 citations*
33. [**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/)
34. **[AI4Research: A Survey of Artificial Intelligence for Scientific Research](https://md.research.elamur.ai/free/en/papers/chen-2025-ai4research-survey-artificial-intelligence/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Mingda Yang, Libo Qin, et al.*2025 · 21 citations*
35. **[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*
36. [**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/)
37. **[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*
38. [**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/)
39. [**Language Models, Agent Models, and World Models: The LAW for Machine Reasoning and Planning arXiv:2312.05230**Zhiting Hu, Tianmin Shu*2023 · 18 citations*](https://md.research.elamur.ai/free/en/papers/hu-2023-language-models-agent-models-world/)
40. **[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*
41. [**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/)
42. **[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*
43. [**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/)
44. [**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/)
45. **[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*

68 more citing papers of our library have no page here yet.

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