--- title: "Who cites A formal proof of the Kepler — 30 citing papers" description: "30 papers of the Elamur Research library cite «A formal proof of the Kepler conjecture», found in their bibliographies; the most cited first." canonical: "https://research.elamur.ai/free/en/papers/hales-2015-formal-proof-kepler-conjecture/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/hales-2015-formal-proof-kepler-conjecture/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [A formal proof of the Kepler conjecture](https://md.research.elamur.ai/free/en/papers/hales-2015-formal-proof-kepler-conjecture/) / cited by # Who cites «A formal proof of the Kepler conjecture» 30 papers of our library cite it (of the 149,439 whose bibliographies we read) · 21 with a page here, the most cited first · [← back to «A formal proof of the Kepler conjecture»](https://md.research.elamur.ai/free/en/papers/hales-2015-formal-proof-kepler-conjecture/) 1. **[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* 2. [**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/) 3. **[HyperTree Proof Search for Neural Theorem Proving](https://md.research.elamur.ai/free/en/papers/lample-2022-hypertree-proof-search-neural-theorem/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Guillaume Lample, Marie-Anne Lachaux, Thibaut Lavril, et al.*2022 · 151 citations* 4. **[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* 5. [**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/) 6. [**Learning to Prove Theorems via Interacting with Proof Assistants arXiv:1905.09381**Kaiyu Yang, Jia Deng*2019 · 90 citations*](https://md.research.elamur.ai/free/en/papers/yang-2019-learning-prove-theorems-interacting-proof/) 7. [**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/) 8. **[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* 9. **[Formalising perfectoid spaces](https://md.research.elamur.ai/free/en/papers/buzzard-2019-formalising-perfectoid-spaces/) [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/)**Kevin Buzzard, Johan Commelin, Patrick Massot*2019 · 48 citations* 10. [**HolStep: A Machine Learning Dataset for Higher-order Logic Theorem Proving arXiv:1703.00426**Cezary Kaliszyk, François Chollet, Christian Szegedy*2017 · 48 citations*](https://md.research.elamur.ai/free/en/papers/kaliszyk-2017-holstep-machine-learning-dataset-higher/) 11. [**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/) 12. [**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/) 13. [**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/) 14. **[Graph Representations for Higher-Order Logic and Theorem Proving](https://md.research.elamur.ai/free/en/papers/paliwal-2019-graph-representations-higher-order-logic/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Aditya Paliwal, Sarah Loos, Markus Rabe, et al.*2019 · 33 citations* 15. [**PaMpeR: Proof Method Recommendation System for Isabelle/HOL arXiv:1806.07239**Yutaka Nagashima, Yilun He*2018 · 29 citations*](https://md.research.elamur.ai/free/en/papers/nagashima-2018-pamper-proof-method-recommendation-system/) 16. [**TacticZero: Learning to Prove Theorems from Scratch with Deep Reinforcement Learning arXiv:2102.09756**Minchao Wu, Michael Norrish, Christian Walder, et al.*2021 · 24 citations*](https://md.research.elamur.ai/free/en/papers/wu-2021-tacticzero-learning-prove-theorems-scratch/) 17. [**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/) 18. **[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* 19. [**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/) 20. [**Proving Olympiad Inequalities by Synergizing LLMs and Symbolic Reasoning arXiv:2502.13834**Zenan Li, Zhaoyu Li, Wen Tang, et al.*2025 · 11 citations*](https://md.research.elamur.ai/free/en/papers/li-2025-proving-olympiad-inequalities-synergizing-llms/) 21. [**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/) 9 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/hales-2015-formal-proof-kepler-conjecture/) — A formal proof of the Kepler conjecture