Pythagoras-Prover: Advancing Efficient Formal Proving via Augmented Lean Formalisation
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 a first proof-of-concept diffusion-based prover (4B) that iteratively refines Lean proofs at inference time. For training efficiency, we build a Lean-verified corpus stratified into easy, medium, a...
| Authors | Joshua Ong Jun Leang, Zheng Zhao, Mihaela Cătălina Stoian et al. |
|---|---|
| Primary category | cs.AI |
| Published | 10 June 2026 |
| Last updated at source | 10 June 2026 |
Connected in the knowledge graph
- Pythagoras-LM/Pythagoras-Prover-4BModel · cited by
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- Pythagoras-LM/SFT_Dataset_Distillation_32BDataset · cited by
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