---
title: "Who cites Leanabell-Prover: Posttraining — 21 citing papers"
description: "21 papers of the Elamur Research library cite «Leanabell-Prover: Posttraining Scaling in Formal Reasoning», found in their bibliographies; the…"
canonical: "https://research.elamur.ai/free/en/papers/zhang-2025-leanabell-prover-posttraining-scaling-formal/cited-by/"
---
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# Who cites «Leanabell-Prover: Posttraining Scaling in Formal Reasoning»

21 papers of our library cite it (of the 149,439 whose bibliographies we read) · 14 with a page here, the most cited first · [← back to «Leanabell-Prover: Posttraining Scaling in Formal Reasoning»](https://md.research.elamur.ai/free/en/papers/zhang-2025-leanabell-prover-posttraining-scaling-formal/)

1. [**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/)
2. [**Kimina-Prover Preview: Towards Large Formal Reasoning Models with Reinforcement Learning arXiv:2504.11354**Haiming Wang, Mert Unsal, Xiaohan Lin, et al.*2025 · 92 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-kimina-prover-preview-large-formal/)
3. **[Aristotle: IMO-level Automated Theorem Proving](https://md.research.elamur.ai/free/en/papers/achim-2025-aristotle-imo-level-automated-theorem/) [SuperIntelligence - Robotics - Safety & Alignment](https://md.research.elamur.ai/free/en/venues/superintelligence-robotics-safety-alignment/)**Tudor Achim, Alex Best, Alberto Bietti, et al.*2025 · 29 citations*
4. [**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/)
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. [**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/)
7. **[Rewarding the Unlikely: Lifting GRPO Beyond Distribution Sharpening](https://md.research.elamur.ai/free/en/papers/he-2025-rewarding-unlikely-lifting-grpo-beyond/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Andre Wang He, Daniel Fried, Sean Welleck*2025 · 15 citations*
8. [**Prover Agent: An Agent-Based Framework for Formal Mathematical Proofs arXiv:2506.19923**Kaito Baba, Chaoran Liu, Shuhei Kurita, et al.*2025 · 14 citations*](https://md.research.elamur.ai/free/en/papers/baba-2025-prover-agent-agent-based-framework/)
9. [**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/)
10. [**REAL-Prover: Retrieval Augmented Lean Prover for Mathematical Reasoning arXiv:2505.20613**Ziju Shen, Naohao Huang, Fanyi Yang, et al.*2025 · 10 citations*](https://md.research.elamur.ai/free/en/papers/shen-2025-real-prover-retrieval-augmented-lean/)
11. **[Reviving DSP for Advanced Theorem Proving in the Era of Reasoning Models](https://md.research.elamur.ai/free/en/papers/cao-2025-reviving-dsp-advanced-theorem-proving/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Chenrui Cao, Liangcheng Song, Zenan Li, et al.*2025 · 7 citations*
12. [**StepFun-Formalizer: Unlocking the Autoformalization Potential of LLMs through Knowledge-Reasoning Fusion arXiv:2508.04440**Yutong Wu, Di Huang, Ruosi Wan, et al.*2025 · 7 citations*](https://md.research.elamur.ai/free/en/papers/wu-2025-stepfun-formalizer-unlocking-autoformalization/)
13. **[miniF2F-Lean Revisited: Reviewing Limitations and Charting a Path Forward](https://md.research.elamur.ai/free/en/papers/ospanov-2025-minif2f-lean-revisited-reviewing-limitations/) [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 · 4 citations*
14. **[MPS-Prover: Advancing Stepwise Theorem Proving by Multi-Perspective Search and Data Curation](https://md.research.elamur.ai/free/en/papers/liang-2025-mps-prover-advancing-stepwise-theorem/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zhenwen Liang, Linfeng Song, Yang Li, et al.*2025 · 4 citations*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/zhang-2025-leanabell-prover-posttraining-scaling-formal/) — Leanabell-Prover: Posttraining Scaling in Formal Reasoning
