--- title: "Who cites LeanReasoner: Boosting — 22 citing papers" description: "22 papers of the Elamur Research library cite «LeanReasoner: Boosting Complex Logical Reasoning with Lean», found in their bibliographies…" canonical: "https://research.elamur.ai/free/en/papers/jiang-2024-leanreasoner-boosting-complex-logical-reasoning/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/jiang-2024-leanreasoner-boosting-complex-logical-reasoning/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [LeanReasoner: Boosting Complex Logical Reasoning…](https://md.research.elamur.ai/free/en/papers/jiang-2024-leanreasoner-boosting-complex-logical-reasoning/) / cited by # Who cites «LeanReasoner: Boosting Complex Logical Reasoning with Lean» 22 papers of our library cite it (of the 149,439 whose bibliographies we read) · 12 with a page here, the most cited first · [← back to «LeanReasoner: Boosting Complex Logical Reasoning with Lean»](https://md.research.elamur.ai/free/en/papers/jiang-2024-leanreasoner-boosting-complex-logical-reasoning/) 1. [**To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoning arXiv:2409.12183**Zayne Sprague, Fangcong Yin, Juan Diego Rodriguez, et al.*2024 · 138 citations*](https://md.research.elamur.ai/free/en/papers/sprague-2024-cot-cot-chain-thought-helps/) 2. **[Verification and Refinement of Natural Language Explanations through LLM-Symbolic Theorem Proving](https://md.research.elamur.ai/free/en/papers/quan-2024-verification-refinement-natural-language-explanations/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xin Quan, Marco Valentino, Louise A. Dennis, et al.*2024 · 52 citations* 3. [**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/) 4. **[Improving Chain-of-Thought Reasoning via Quasi-Symbolic Abstractions](https://md.research.elamur.ai/free/en/papers/ranaldi-2025-improving-chain-thought-reasoning-quasi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Leonardo Ranaldi, Marco Valentino, Andre Freitas*2025 · 42 citations* 5. **[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* 6. **[Safe: Enhancing Mathematical Reasoning in Large Language Models via Retrospective Step-aware Formal Verification](https://md.research.elamur.ai/free/en/papers/liu-2025-safe-enhancing-mathematical-reasoning-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chengwu Liu, Ye Yuan, Yichun Yin, et al.*2025 · 17 citations* 7. **[CoMAT: Chain of Mathematically Annotated Thought Improves Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/leang-2025-comat-chain-mathematically-annotated-thought/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Joshua Ong Jun Leang, Aryo Pradipta Gema, Shay B. Cohen*2025 · 14 citations* 8. **[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* 9. **[Theorem Prover as a Judge for Synthetic Data Generation](https://md.research.elamur.ai/free/en/papers/leang-2025-theorem-prover-as-judge-synthetic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Joshua Ong Jun Leang, Giwon Hong, Wenda Li, et al.*2025 · 9 citations* 10. [**Brains vs. Bytes: Evaluating LLM Proficiency in Olympiad Mathematics arXiv:2504.01995**Hamed Mahdavi, Alireza Hashemi, Majid Daliri, et al.*2025 · 8 citations*](https://md.research.elamur.ai/free/en/papers/mahdavi-2025-brains-vs-bytes-evaluating-llm/) 11. **[Thinking in Schemas: Robust Syllogistic Reasoning in LLMs](https://md.research.elamur.ai/free/en/papers/ranaldi-2026-thinking-schemas-robust-syllogistic-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Federico Ranaldi, Leonardo Ranaldi, Fabio Massimo Zanzotto, et al.*2026* 12. **[Towards Trustworthy Smart Contract Synthesis: A Multi-Agent Framework with Lean-Based Verification](https://md.research.elamur.ai/free/en/papers/zhang-2026-trustworthy-smart-contract-synthesis-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bowei Zhang, Hanbing Liu, Qixin Tian, et al.*2026* 10 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/jiang-2024-leanreasoner-boosting-complex-logical-reasoning/) — LeanReasoner: Boosting Complex Logical Reasoning with Lean