---
title: "Who cites Lawrence C. Paulson — 84 papers of our library"
description: "84 papers of the Elamur Research library cite the works of Lawrence C. Paulson, found in their bibliographies; the most cited first."
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---
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# Who cites Lawrence C. Paulson

95 citations of their works from 84 papers of our library (of the 149,439 whose bibliographies we read) · 57 with a page here, the most cited first · [← Lawrence C. Paulson](https://md.research.elamur.ai/free/en/authors/lawrence-c-paulson/)

1. [**On the Opportunities and Risks of Foundation Models arXiv:2108.07258**Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, et al.*2021 · 3,160 citations*](https://md.research.elamur.ai/free/en/papers/bommasani-2021-opportunities-risks-foundation-models/)
2. [**Measuring Mathematical Problem Solving With the MATH Dataset arXiv:2103.03874**Dan Hendrycks, Collin Burns, Saurav Kadavath, et al.*2021 · 2,395 citations*](https://md.research.elamur.ai/free/en/papers/hendrycks-2021-measuring-mathematical-problem-solving-math/)
3. [**DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models arXiv:2402.03300**Zhihong Shao, Peiyi Wang, Qihao Zhu, et al.*2024 · 2,115 citations*](https://md.research.elamur.ai/free/en/papers/shao-2024-deepseekmath-pushing-limits-mathematical-reasoning/)
4. **[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*
5. [**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/)
6. **[Large Language Models for Mathematical Reasoning: Progresses and Challenges](https://md.research.elamur.ai/free/en/papers/ahn-2024-large-language-models-mathematical-reasoning/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Janice Ahn, Rishu Verma, Renze Lou, et al.*2024 · 280 citations*
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. **[The Lean mathematical library](https://md.research.elamur.ai/free/en/papers/community-2019-lean-mathematical-library/) [ACM SIGPLAN International Conference on Certified Programs and Proofs (CPP)](https://md.research.elamur.ai/free/en/venues/acm-sigplan-international-conference-on-certified-programs-and-proofs-cpp/)**The mathlib Community*2019 · 249 citations*
9. [**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/)
10. **[LILA: A Unified Benchmark for Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/mishra-2022-lila-unified-benchmark-mathematical-reasoning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Swaroop Mishra, Matthew Finlayson, Pan Lu, et al.*2022 · 179 citations*
11. [**DeepMath - Deep Sequence Models for Premise Selection arXiv:1606.04442**Alex A. Alemi, Francois Chollet, Niklas Een, et al.*2016 · 178 citations*](https://md.research.elamur.ai/free/en/papers/alemi-2016-deepmath-deep-sequence-models-premise/)
12. **[Deep Network Guided Proof Search](https://md.research.elamur.ai/free/en/papers/loos-2017-deep-network-guided-proof-search/) [EPiC series in computing](https://md.research.elamur.ai/free/en/venues/epic-series-in-computing/)**Sarah Loos, Geoffrey Irving, Christian Szegedy, et al.*2017 · 139 citations*
13. [**Formal Mathematics Statement Curriculum Learning arXiv:2202.01344**Stanislas Polu, Jesse Michael Han, Kunhao Zheng, et al.*2022 · 133 citations*](https://md.research.elamur.ai/free/en/papers/polu-2022-formal-mathematics-statement-curriculum-learning/)
14. **[UniGeo: Unifying Geometry Logical Reasoning via Reformulating Mathematical Expression](https://md.research.elamur.ai/free/en/papers/chen-2022-unigeo-unifying-geometry-logical-reasoning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jiaqi Chen, Tong Li, Jinghui Qin, et al.*2022 · 111 citations*
15. **[Faster, Higher, Stronger: E 2.3](https://md.research.elamur.ai/free/en/papers/schulz-2019-faster-higher-stronger-e-2/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Stephan Schulz, Simon Cruanes, Petar Vukmirović*2019 · 111 citations*
16. [**Premise Selection for Theorem Proving by Deep Graph Embedding arXiv:1709.09994**Mingzhe Wang, Yihe Tang, Jian Wang, et al.*2017 · 106 citations*](https://md.research.elamur.ai/free/en/papers/wang-2017-premise-selection-theorem-proving-deep/)
17. [**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/)
18. **[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*
19. [**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/)
20. [**Proof Artifact Co-training for Theorem Proving with Language Models arXiv:2102.06203**Jesse Michael Han, Jason Rute, Yuhuai Wu, et al.*2021 · 82 citations*](https://md.research.elamur.ai/free/en/papers/han-2021-proof-artifact-co-training-theorem/)
21. **[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*
22. [**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/)
23. [**Thor: Wielding Hammers to Integrate Language Models and Automated Theorem Provers arXiv:2205.10893**Albert Q. Jiang, Wenda Li, Szymon Tworkowski, et al.*2022 · 79 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2022-thor-wielding-hammers-integrate-language/)
24. [**HOList: An Environment for Machine Learning of Higher-Order Theorem Proving arXiv:1904.03241**Kshitij Bansal, Sarah M. Loos, Markus N. Rabe, et al.*2019 · 78 citations*](https://md.research.elamur.ai/free/en/papers/bansal-2019-holist-environment-machine-learning-higher/)
25. [**NaturalProofs: Mathematical Theorem Proving in Natural Language arXiv:2104.01112**Sean Welleck, Jiacheng Liu, Ronan Le Bras, et al.*2021 · 76 citations*](https://md.research.elamur.ai/free/en/papers/welleck-2021-naturalproofs-mathematical-theorem-proving-natural/)
26. **[ENIGMA: Efficient Learning-based Inference Guiding Machine](https://md.research.elamur.ai/free/en/papers/jakubuv-2017-enigma-efficient-learning-based-inference/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Jan Jakubův, Josef Urban*2017 · 67 citations*
27. **[First Experiments with Neural Translation of Informal to Formal Mathematics](https://md.research.elamur.ai/free/en/papers/wang-2018-first-experiments-neural-translation-informal/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Qingxiang Wang, Cezary Kaliszyk, Josef Urban*2018 · 66 citations*
28. **[ENIGMA-NG: Efficient Neural and Gradient-Boosted Inference Guidance for E](https://md.research.elamur.ai/free/en/papers/chvalovsky-2019-enigma-ng-efficient-neural-gradient/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Karel Chvalovský, Jan Jakubův, Martin Suda, et al.*2019 · 61 citations*
29. **[TacticToe: Learning to Prove with Tactics](https://md.research.elamur.ai/free/en/papers/gauthier-2018-tactictoe-learning-prove-tactics/) [Journal of Automated Reasoning](https://md.research.elamur.ai/free/en/venues/journal-of-automated-reasoning/)**Thibault Gauthier, Cezary Kaliszyk, Josef Urban, et al.*2018 · 57 citations*
30. [**Mathematical Reasoning via Self-supervised Skip-tree Training arXiv:2006.04757**Markus N. Rabe, Dennis Lee, Kshitij Bansal, et al.*2020 · 54 citations*](https://md.research.elamur.ai/free/en/papers/rabe-2020-mathematical-reasoning-self-supervised-skip/)
31. [**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/)
32. [**Reinforcement Learning of Theorem Proving arXiv:1805.07563**Cezary Kaliszyk, Josef Urban, Henryk Michalewski, et al.*2018 · 50 citations*](https://md.research.elamur.ai/free/en/papers/kaliszyk-2018-reinforcement-learning-theorem-proving/)
33. [**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/)
34. **[ENIGMA Anonymous: Symbol-Independent Inference Guiding Machine (system description)](https://md.research.elamur.ai/free/en/papers/jakubuv-2020-enigma-anonymous-symbol-independent-inference/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Jan Jakubův, Karel Chvalovský, Miroslav Olšák, et al.*2020 · 42 citations*
35. [**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/)
36. **[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*
37. [**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/)
38. [**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/)
39. [**Learning to Reason in Large Theories without Imitation arXiv:1905.10501**Kshitij Bansal, Christian Szegedy, Markus N. Rabe, et al.*2019 · 36 citations*](https://md.research.elamur.ai/free/en/papers/bansal-2019-learning-reason-large-theories-without/)
40. [**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/)
41. [**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/)
42. **[Property Invariant Embedding for Automated Reasoning](https://md.research.elamur.ai/free/en/papers/olsak-2019-property-invariant-embedding-automated-reasoning/) [Frontiers in artificial intelligence and applications](https://md.research.elamur.ai/free/en/venues/frontiers-in-artificial-intelligence-and-applications/)**Miroslav Olšák, Cezary Kaliszyk, Josef Urban*2019 · 30 citations*
43. [**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/)
44. [**Teaching Temporal Logics to Neural Networks arXiv:2003.04218**Christopher Hahn, Frederik Schmitt, Jens U. Kreber, et al.*2020 · 24 citations*](https://md.research.elamur.ai/free/en/papers/hahn-2020-teaching-temporal-logics-neural-networks/)
45. [**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/)
46. [**LLMSTEP: LLM proofstep suggestions in Lean arXiv:2310.18457**Sean Welleck, Rahul Saha*2023 · 22 citations*](https://md.research.elamur.ai/free/en/papers/welleck-2023-llmstep-llm-proofstep-suggestions-lean/)
47. **[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*
48. **[Stateful Premise Selection by Recurrent Neural Networks](https://md.research.elamur.ai/free/en/papers/piotrowski-2020-stateful-premise-selection-recurrent-neural/) [EPiC series in computing](https://md.research.elamur.ai/free/en/venues/epic-series-in-computing/)**Bartosz Piotrowski, Josef Urban*2020 · 21 citations*
49. [**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/)
50. [**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/)
51. [**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/)
52. **[Deep Reinforcement Learning for Synthesizing Functions in Higher-Order Logic](https://md.research.elamur.ai/free/en/papers/gauthier-2019-deep-reinforcement-learning-synthesizing-functions/) [EPiC series in computing](https://md.research.elamur.ai/free/en/venues/epic-series-in-computing/)**Thibault Gauthier*2019 · 15 citations*
53. **[A Symbolic Framework for Evaluating Mathematical Reasoning and Generalisation with Transformers](https://md.research.elamur.ai/free/en/papers/meadows-2024-symbolic-framework-evaluating-mathematical-reasoning/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Jordan Meadows, Marco Valentino, Damien Teney, et al.*2024 · 14 citations*
54. **[Proving Olympiad Algebraic Inequalities without Human Demonstrations](https://md.research.elamur.ai/free/en/papers/wei-2024-proving-olympiad-algebraic-inequalities-without/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Chenrui Wei, Mengzhou Sun, Wei Wang*2024 · 12 citations*
55. **[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*
56. [**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/)
57. [**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/)

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

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