Learning to Reason with Insight: Training LLMs to Generate Key Proof Intuitions Before Attempting Proofs

arXiv·medium signal

Li et al. identify a bottleneck in LLM informal theorem proving: models follow proof steps but struggle to generate the key insight that unlocks a proof. Their approach explicitly trains models to produce reasoning insights before attempting solutions, mirroring how mathematicians work. Relevant as reasoning capabilities become the primary differentiator in frontier model evaluations.