---
title: "Who cites Decomposing the Enigma: — 27 citing papers"
description: "27 papers of the Elamur Research library cite «Decomposing the Enigma: Subgoal-based Demonstration Learning for Formal Theorem…"
canonical: "https://research.elamur.ai/free/en/papers/zhao-2023-decomposing-enigma-subgoal-based-demonstration/cited-by/"
---
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# Who cites «Decomposing the Enigma: Subgoal-based Demonstration Learning for Formal Theorem Proving»

27 papers of our library cite it (of the 149,439 whose bibliographies we read) · 19 with a page here, the most cited first · [← back to «Decomposing the Enigma: Subgoal-based Demonstration Learning for Formal Theorem Proving»](https://md.research.elamur.ai/free/en/papers/zhao-2023-decomposing-enigma-subgoal-based-demonstration/)

1. **[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*
2. [**DeepSeek-Prover-V2: Advancing Formal Mathematical Reasoning via Reinforcement Learning for Subgoal Decomposition arXiv:2504.21801**Z. Z. Ren, Zhihong Shao, Junxiao Song, et al.*2025 · 122 citations*](https://md.research.elamur.ai/free/en/papers/ren-2025-deepseek-prover-v2-advancing-formal/)
3. [**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/)
4. [**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/)
5. **[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*
6. [**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/)
7. [**G-LLaVA: Solving Geometric Problem with Multi-Modal Large Language Model arXiv:2312.11370**Jiahui Gao, Renjie Pi, Jipeng Zhang, et al.*2023 · 76 citations*](https://md.research.elamur.ai/free/en/papers/gao-2023-g-llava-solving-geometric-problem/)
8. [**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/)
9. [**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/)
10. [**Hilbert: Recursively Building Formal Proofs with Informal Reasoning arXiv:2509.22819**Sumanth Varambally, Thomas Voice, Yanchao Sun, et al.*2025 · 26 citations*](https://md.research.elamur.ai/free/en/papers/varambally-2025-hilbert-recursively-building-formal-proofs/)
11. [**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/)
12. [**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/)
13. **[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*
14. **[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*
15. [**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/)
16. [**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/)
17. [**Mathesis: Towards Formal Theorem Proving from Natural Languages arXiv:2506.07047**Yu Xuejun, Jianyuan Zhong, Zijin Feng, et al.*2025 · 9 citations*](https://md.research.elamur.ai/free/en/papers/xuejun-2025-mathesis-towards-formal-theorem-proving/)
18. [**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/)
19. **[Learning from Cognition: Enhancing RL Efficiency for LLM Reasoning via Hierarchical Metacognitive Decomposition and Refinement](https://md.research.elamur.ai/free/en/papers/sun-2026-learning-cognition-enhancing-rl-efficiency/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zexu Sun, Yongcheng Zeng, Erxue Min, et al.*2026*

8 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/zhao-2023-decomposing-enigma-subgoal-based-demonstration/) — Decomposing the Enigma: Subgoal-based Demonstration Learning for Formal Theorem Proving
