--- title: "Who cites Holophrasm: a neural Automated — 26 citing papers" description: "26 papers of the Elamur Research library cite «Holophrasm: a neural Automated Theorem Prover for higher-order logic», found in their…" canonical: "https://research.elamur.ai/free/en/papers/whalen-2016-holophrasm-neural-automated-theorem-prover/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/whalen-2016-holophrasm-neural-automated-theorem-prover/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Holophrasm: a neural Automated Theorem Prover for…](https://md.research.elamur.ai/free/en/papers/whalen-2016-holophrasm-neural-automated-theorem-prover/) / cited by # Who cites «Holophrasm: a neural Automated Theorem Prover for higher-order logic» 26 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 «Holophrasm: a neural Automated Theorem Prover for higher-order logic»](https://md.research.elamur.ai/free/en/papers/whalen-2016-holophrasm-neural-automated-theorem-prover/) 1. [**MiniF2F: a cross-system benchmark for formal Olympiad-level mathematics arXiv:2109.00110**Kunhao Zheng, Jesse Michael Han, Stanislas Polu*2021 · 257 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2021-minif2f-cross-system-benchmark-formal/) 2. [**Generative Language Modeling for Automated Theorem Proving arXiv:2009.03393**Stanislas Polu, Ilya Sutskever*2020 · 241 citations*](https://md.research.elamur.ai/free/en/papers/polu-2020-generative-language-modeling-automated-theorem/) 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. [**GamePad: A Learning Environment for Theorem Proving arXiv:1806.00608**Daniel Huang, Prafulla Dhariwal, Dawn Song, et al.*2018 · 94 citations*](https://md.research.elamur.ai/free/en/papers/huang-2018-gamepad-learning-environment-theorem-proving/) 7. [**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/) 8. [**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/) 9. [**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/) 10. [**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/) 11. [**Learning to Prove Theorems by Learning to Generate Theorems arXiv:2002.07019**Mingzhe Wang, Jia Deng*2020 · 53 citations*](https://md.research.elamur.ai/free/en/papers/wang-2020-learning-prove-theorems-learning-generate/) 12. [**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/) 13. [**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/) 14. [**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/) 15. **[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* 16. [**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/) 17. [**Metamath: A Computer Language for Mathematical Proofs Lulu Press (2nd ed.)**Norman Megill, David A. Wheeler*2019 · 25 citations*](https://md.research.elamur.ai/free/en/papers/megill-2019-metamath-computer-language-mathematical-proofs/) 18. **[Learning Formal Mathematics From Intrinsic Motivation](https://md.research.elamur.ai/free/en/papers/poesia-2024-learning-formal-mathematics-intrinsic-motivation/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Gabriel Poesia, David Broman, Nick Haber, et al.*2024 · 23 citations* 19. [**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/) 20. [**Guiding High-Performance SAT Solvers with Unsat-Core Predictions arXiv:1903.04671 (International Conference on Theory and Applications of Satisfiability Testing. Springer, Cham, 2019)**Daniel Selsam, Nikolaj Bjørner*2019 · 16 citations*](https://md.research.elamur.ai/free/en/papers/selsam-2019-guiding-high-performance-sat-solvers/) 21. [**Automated Theorem Proving in Intuitionistic Propositional Logic by Deep Reinforcement Learning arXiv:1811.00796**Mitsuru Kusumoto, Keisuke Yahata, Masahiro Sakai*2018 · 15 citations*](https://md.research.elamur.ai/free/en/papers/kusumoto-2018-automated-theorem-proving-intuitionistic-propositional/) 5 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/whalen-2016-holophrasm-neural-automated-theorem-prover/) — Holophrasm: a neural Automated Theorem Prover for higher-order logic