---
title: "Who cites Leonardo de Moura — 210 papers of our library"
description: "210 papers of the Elamur Research library cite the works of Leonardo de Moura, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/leonardo-de-moura/cited-by/"
---
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# Who cites Leonardo de Moura

211 citations of their works from 210 papers of our library (of the 149,439 whose bibliographies we read) · 35 with a page here, the most cited first · [← Leonardo de Moura](https://md.research.elamur.ai/free/en/authors/leonardo-de-moura/)

1. [**Relational inductive biases, deep learning, and graph networks arXiv:1806.01261**Peter W. Battaglia, Jessica B. Hamrick, Victor Bapst, et al.*2018 · 2,335 citations*](https://md.research.elamur.ai/free/en/papers/battaglia-2018-relational-inductive-biases-deep-learning/)
2. [**Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models arXiv:2206.04615 · Transactions on Machine Learning Research, May/2022, https://openreview.net/forum?id=uyTL5Bvosj**Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao, et al.*2022 · 1,756 citations*](https://md.research.elamur.ai/free/en/papers/srivastava-2022-imitation-game-quantifying-extrapolating-capabilities/)
3. [**Evaluating Models' Local Decision Boundaries via Contrast Sets**Matt Gardner, Yoav Artzi, Victoria Basmov, et al.*2020 · 531 citations*](https://md.research.elamur.ai/free/en/papers/gardner-2020-evaluating-models-local-decision-boundaries/)
4. **[Transformers as Soft Reasoners over Language](https://md.research.elamur.ai/free/en/papers/clark-2020-transformers-soft-reasoners-over-language/) [International Joint Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/international-joint-conference-on-artificial-intelligence/)**Peter Clark, Oyvind Tafjord, Kyle Richardson*2020 · 382 citations*
5. **[ProofWriter: Generating Implications, Proofs, and Abductive Statements over Natural Language](https://md.research.elamur.ai/free/en/papers/tafjord-2021-proofwriter-generating-implications-proofs-abductive/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Oyvind Tafjord, Bhavana Dalvi, Peter Clark*2021 · 335 citations*
6. [**Analysing Mathematical Reasoning Abilities of Neural Models arXiv:1904.01557**David Saxton, Edward Grefenstette, Felix Hill, et al.*2019 · 288 citations*](https://md.research.elamur.ai/free/en/papers/saxton-2019-analysing-mathematical-reasoning-abilities-neural/)
7. [**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/)
8. **[What Can Transformers Learn In-Context? A Case Study of Simple Function Classes](https://md.research.elamur.ai/free/en/papers/garg-2022-transformers-learn-context-case-study/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Shivam Garg, Dimitris Tsipras, Percy Liang, et al.*2022 · 209 citations*
9. [**Formal Mathematics Statement Curriculum Learning arXiv:2202.01344**Stanislas Polu, Jesse Michael Han, Kunhao Zheng, et al.*2022 · 133 citations*](https://md.research.elamur.ai/free/en/papers/polu-2022-formal-mathematics-statement-curriculum-learning/)
10. [**DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence arXiv:2606.19348**DeepSeek-AI, Anyi Xu, Bangcai Lin, et al.*2026 · 122 citations*](https://md.research.elamur.ai/free/en/papers/deepseek-ai-2026-deepseek-v4-highly-efficient/)
11. [**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/)
12. [**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/)
13. [**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/)
14. **[PRover: Proof Generation for Interpretable Reasoning over Rules](https://md.research.elamur.ai/free/en/papers/saha-2020-prover-proof-generation-interpretable-reasoning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Swarnadeep Saha, Sayan Ghosh, Shashank Srivastava, et al.*2020 · 103 citations*
15. **[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*
16. [**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/)
17. [**InternLM-Math: Open Math Large Language Models Toward Verifiable Reasoning arXiv:2402.06332**Huaiyuan Ying, Shuo Zhang, Linyang Li, et al.*2024 · 90 citations*](https://md.research.elamur.ai/free/en/papers/ying-2024-internlm-math-open-math-large/)
18. [**Goedel-Prover: A Frontier Model for Open-Source Automated Theorem Proving arXiv:2502.07640**Yong Lin, Shange Tang, Bohan Lyu, et al.*2025 · 84 citations*](https://md.research.elamur.ai/free/en/papers/lin-2025-goedel-prover-frontier-model-open/)
19. **[Lean Workbook: A large-scale Lean problem set formalized from natural language math problems](https://md.research.elamur.ai/free/en/papers/ying-2024-lean-workbook-large-scale-lean/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Huaiyuan Ying, Zijian Wu, Yihan Geng, et al.*2024 · 80 citations*
20. [**Goedel-Prover-V2: Scaling Formal Theorem Proving with Scaffolded Data Synthesis and Self-Correction arXiv:2508.03613**Yong Lin, Shange Tang, Bohan Lyu, et al.*2025 · 67 citations*](https://md.research.elamur.ai/free/en/papers/lin-2025-goedel-prover-v2-scaling-formal/)
21. [**HunyuanProver: A Scalable Data Synthesis Framework and Guided Tree Search for Automated Theorem Proving arXiv:2412.20735**Yang Li, Dong Du, Linfeng Song, et al.*2024 · 25 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-hunyuanprover-scalable-data-synthesis/)
22. [**Seed-Prover 1.5: Mastering Undergraduate-Level Theorem Proving via Learning from Experience arXiv:2512.17260**Jiangjie Chen, Wenxiang Chen, Jiacheng Du, et al.*2025 · 19 citations*](https://md.research.elamur.ai/free/en/papers/chen-2025-seed-prover-1-5/)
23. [**MA-LoT: Model-Collaboration Lean-based Long Chain-of-Thought Reasoning enhances Formal Theorem Proving arXiv:2503.03205**Ruida Wang, Rui Pan, Yuxin Li, et al.*2025 · 18 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-ma-lot-model-collaboration-lean/)
24. [**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/)
25. **[ATLAS: Autoformalizing Theorems through Lifting, Augmentation, and Synthesis of Data](https://md.research.elamur.ai/free/en/papers/liu-2025-atlas-autoformalizing-theorems-through-lifting/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Xiaoyang Liu, Kangjie Bao, Jiashuo Zhang, et al.*2025 · 16 citations*
26. **[A Semantic Search Engine for Mathlib4](https://md.research.elamur.ai/free/en/papers/gao-2024-semantic-search-engine-mathlib4/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Guoxiong Gao, Haocheng Ju, Jiedong Jiang, et al.*2024 · 14 citations*
27. **[CriticLean: Critic-Guided Reinforcement Learning for Mathematical Formalization](https://md.research.elamur.ai/free/en/papers/peng-2026-criticlean-critic-guided-reinforcement-learning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhongyuan Peng, Yifan Yao, Kaijing Ma, et al.*2026 · 12 citations*
28. [**The Open Proof Corpus: A Large-Scale Study of LLM-Generated Mathematical Proofs arXiv:2506.21621**Jasper Dekoninck, Ivo Petrov, Kristian Minchev, et al.*2025 · 11 citations*](https://md.research.elamur.ai/free/en/papers/dekoninck-2025-open-proof-corpus-large-scale/)
29. [**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/)
30. **[Examining False Positives under Inference Scaling for Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/wang-2025-examining-false-positives-under-inference/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yu Wang, Nan Yang, Liang Wang, et al.*2025 · 9 citations*
31. **[Let's Reason Formally: Natural-Formal Hybrid Reasoning Enhances LLM's Math Capability](https://md.research.elamur.ai/free/en/papers/wang-2025-let-s-reason-formally-natural/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ruida Wang, Yuxin Li, Yi R. Fung, et al.*2025 · 7 citations*
32. [**GFLean: An Autoformalisation Framework for Lean via GF arXiv:2404.01234**Shashank Pathak*2024 · 5 citations*](https://md.research.elamur.ai/free/en/papers/pathak-2024-gflean-autoformalisation-framework-lean-gf/)
33. **[SATQuest: A Verifier for Logical Reasoning Evaluation and Reinforcement Fine-Tuning of LLMs](https://md.research.elamur.ai/free/en/papers/zhao-2026-satquest-verifier-logical-reasoning-evaluation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yanxiao Zhao, Yaqian Li, Zihao Bo, et al.*2026*
34. **[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*
35. **[Methods for Constraint Solving Problems Based on Learn to Reason Model: A Review (基于学习-推理的约束求解方法研究进展)](https://md.research.elamur.ai/free/en/papers/zou-2023-methods-constraint-solving/) [Journal of Software](https://md.research.elamur.ai/free/en/venues/journal-of-software/)**Yue Zou (邹悦), Jiayang Lai (赖家洋), Yonggang Zhang (张永刚)*2023*

175 more citing papers of our library have no page here yet.

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