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LongCat-Flash-Prover Open Source Release: Formal Inference Model Analysis for Lean4

LongCat-Flash-Prover Open Source Release: Formal Inference Model Analysis for Lean4

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  1. Abstract

LongCat-Flash-Prover is an open-source formal reasoning model from the Meituan LongCat team, which is aimed at mathematical proof tasks in the Lean4 environment. The project adopts a 560B-parameter MoE architecture that focuses on solving the whole process from informal questions to formal expressions, proof sketches, and complete proofs. It emphasizes reducing error rates in long-link proofs through tool integration reasoning and achieving strong results on multiple open-source theorem proof benchmarks.

  1. Core features
  2. Native formal reasoning: Regard formal reasoning as the core capability of the model, rather than a simple natural language chain thinking extension.
  3. Three-stage capability splitting: covering auto-formalization, sketching, and proving, corresponding to formal expressions, proof sketches, and complete proofs, respectively.
  4. Hybrid-Experts Iteration Framework: Used to construct large-scale, high-quality formal trajectory data and improve the quality of training samples.
  5. HisPO algorithm: used to stabilize long-term tool-integrated reasoning training, adapting to the strict feedback mechanism of formal reasoning.
  6. Strict verification pipeline: Combined with Lean4, theorem consistency check, and legitimacy detection, it reduces the problem of hallucinatory proofs and reward speculation.
  7. Installation
  8. Get the LongCat-Flash-Prover repository and usage instructions from the official GitHub.
  9. Prepare inference and verification dependencies according to the official environment requirements, and the core scenario revolves around the Lean4 toolchain.
  10. Get the model weights from Hugging Face and organize the inputs according to the official template.
  11. Due to the large scale of the model, the actual deployment is more suitable for environments with high-performance GPUs and complete inference infrastructure.
  12. Typical use cases
  13. Mathematical Theorem Proofs: Generate verifiable formal proofs in Lean4.
  14. Automatic formalization: convert natural language math problems into formal statements.
  15. Proof sketch generation: Mr. into a lemma style sketch, and then gradually complete the complete proof.
  16. Research assistance: used for formal mathematics, theorem proof process design and reasoning system evaluation.
  17. Ecology and competing products
  18. In terms of ecology, the project has provided GitHub, Hugging Face, and paper pages to facilitate researchers' reproduction and evaluation.
  19. Compared with the direct output of mathematical answers by general large models, LongCat-Flash-Prover emphasizes verifiable results in Lean4.
  20. Compared with open source models that only do natural language mathematical reasoning, its differences are tool integration reasoning, formal goals, and strict verification processes.
  21. Limitations and precautions
  22. This project is mainly oriented to formal mathematics and the Lean4 ecosystem, and is not equivalent to general chat or ordinary mathematical question and answer model.
  23. The scale of the model is large, and the deployment, inference cost and engineering complexity are high.
  24. Even if the verification mechanism is introduced, the performance under different data sets, budgets and attempts still needs to be understood in combination with actual evaluation.
  25. Formal proofs rely on specific toolchains and syntax environments, and cannot be directly equivalent when migrating to other proof assistants.
  26. Project address

https://github.com/meituan-longcat/LongCat-Flash-Prover⁠

  1. Frequently asked questions

Q: What is the LongCat-Flash-Prover?

A: LongCat-Flash-Prover is an open-source formalized reasoning model for Lean4 that focuses on mathematical theorem proofing, automatic formalization, and proof generation.

Q: What does LongCat-Flash-Prover's HisPO algorithm do?

A: HisPO is used to stabilize long-duration tool-integrated reasoning training and reduce training instability in formal reasoning tasks.

Q: What core tasks does LongCat-Flash-Prover support?

A: It supports three types of core tasks: auto-formalization, sketching, and proving, corresponding to formal expressions, proof sketches, and full proofs.

Q: What are the benchmark scores for LongCat-Flash-Prover?

A: Official public results show that it has strong open-source results on tasks such as MiniF2F-Test, ProverBench, and PutnamBench.

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