Kimina-Prover: Applying Test-time RL Search on Large Formal Reasoning Models

Kimina-Prover-72B uses a Test-Time Reinforcement Learning (TTRL) search to autonomously discover and reuse lemmas for long-horizon Lean proofs, plus an error-fixing module that interprets Lean messages for targeted corrections. It achieves a state-of-the-art miniF2F performance (92.2% pass rate) and shows pass@1/32/1024 of 63.9/84.0/87.7, with two distilled variants released (8B and 1.7B).

Source

HuggingFace Blog

Ingéré

10 JUIL. 2025 · 19:10

Score édito

4.0 / 5