mlsanityData to 14 Oct 2026

Lean4Physics: Comprehensive Reasoning Framework for College-level Physics in Lean4

arXiv 2510.26094 ↗First posted 30 Oct 2025cs.AI cs.LGcited by 5

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Abstract (arXiv)

We present **Lean4PHYS**, a comprehensive reasoning framework for college-level physics problems in Lean4. **Lean4PHYS** includes *LeanPhysBench*, a college-level benchmark for formal physics reasoning in Lean4, which contains 200 hand-crafted and peer-reviewed statements derived from university textbooks and physics competition problems. To establish a solid foundation for formal reasoning in physics, we also introduce *PhysLib*, a community-driven repository containing fundamental unit systems and theorems essential for formal physics reasoning. Based on the benchmark and Lean4 repository we composed in **Lean4PHYS**, we report baseline results using major expert Math Lean4 provers and state-of-the-art closed-source models, with the best performance of DeepSeek-Prover-V2-7B achieving only 16% and Claude-Sonnet-4 achieving 35%. We also conduct a detailed analysis showing that our *PhysLib* can achieve an average improvement of 11.75% in model performance. This demonstrates the challenging nature of our *LeanPhysBench* and the effectiveness of *PhysLib*. To the best of our knowledge, this is the first study to provide a physics benchmark in Lean4.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 33 of its 54 references that are in the map. First posted on arXiv 30 Oct 2025.

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33 of 54 references.

References · 33

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  10. 2021MiniF2F: a cross-system benchmark for formal Olympiad-level mathematicscited by 391
  11. 2025DeepSeek-Prover-V2: Advancing Formal Mathematical Reasoning via Reinforcement Learning for Subgoal Decompositioncited by 287
  12. 2024DeepSeek-Prover-V1.5: Harnessing Proof Assistant Feedback for Reinforcement Learning and Monte-Carlo Tree Searchcited by 197
21 more
  1. 2023ProofNet: Autoformalizing and Formally Proving Undergraduate-Level Mathematicscited by 192
  2. 2025Kimina-Prover Preview: Towards Large Formal Reasoning Models with Reinforcement Learningcited by 180
  3. 2025Goedel-Prover-V2: Scaling Formal Theorem Proving with Scaffolded Data Synthesis and Self-Correctioncited by 154
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  6. 2025Goedel-Prover: A Frontier Model for Open-Source Automated Theorem Provingcited by 133
  7. 2024Lean Workbook: A large-scale Lean problem set formalized from natural language math problemscited by 122
  8. 2025BFS-Prover: Scalable Best-First Tree Search for LLM-based Automatic Theorem Provingcited by 84
  9. 2025STP: Self-play LLM Theorem Provers with Iterative Conjecturing and Provingcited by 79
  10. 2024TheoremLlama: Transforming General-Purpose LLMs into Lean4 Expertscited by 59
  11. 2025PhysReason: A Comprehensive Benchmark towards Physics-Based Reasoningcited by 59
  12. 2025AdaCtrl: Towards Adaptive and Controllable Reasoning via Difficulty-Aware Budgetingcited by 50
  13. 2025UGPhysics: A Comprehensive Benchmark for Undergraduate Physics Reasoning with Large Language Modelscited by 48
  14. 2025MA-LoT: Model-Collaboration Lean-based Long Chain-of-Thought Reasoning enhances Formal Theorem Provingcited by 24
  15. 2025HiPhO: How Far Are (M)LLMs from Humans in the Latest High School Physics Olympiad Benchmark?cited by 19
  16. 2025Scaling Physical Reasoning with the PHYSICS Datasetcited by 13
  17. 2025MATP-BENCH: Can MLLM Be a Good Automated Theorem Prover for Multimodal Problems?cited by 13
  18. 2025Let's Reason Formally: Natural-Formal Hybrid Reasoning Enhances LLM's Math Capabilitycited by 11
  19. 2024HepLean: Digitalising high energy physicscited by 10
  20. 2022Formalizing Chemical Physics using the Lean Theorem Provercited by 9
  21. 2025Veri-R1: Toward Precise and Faithful Claim Verification via Online Reinforcement Learningcited by 5

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Citing papers per year: 2026: 5.

5 papers.