Pythagoras-Prover: Advancing Efficient Formal Proving via Augmented Lean Formalisation
Quick Answer
Pythagoras-Prover introduces a compute-efficient family of Lean theorem provers, outperforming DeepSeek-Prover-V2-671B with 167x fewer parameters and achieving 93.0% on MiniF2F-Test.
Quick Take
The 4B model surpasses previous benchmarks, demonstrating effective training strategies and augmented formalization techniques.
Key Points
- Pythagoras-Prover includes autoregressive models with 4B and 32B parameters.
- The 32B model sets the open-source state of the art at 93.0% on MiniF2F-Test.
- Pythagoras-Prover-4B achieves 86.1% on MiniF2F-Test with significantly fewer parameters.
- Augmented Lean Formalisation (ALF) enhances training data without formal verification.
- Dynamic proof-reasoning filtering maintains informative proof traces within an 8k-token context.
Paper Resources
Source Excerpt
Modern Lean theorem provers achieve strong performance only with substantial training and inference compute, driven in part by scarce verified proof data and the long reasoning traces of formal proof search, making both supervised fine-tuning (SFT) and sampling expensive. We introduce Pythagoras-Prover, a compute-efficient open-source family of Lean theorem provers built for practical compute budgets. The family spans two generation paradigms: autoregressive models at 4B and 32B parameters, and
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