Progressive Multi-Stage SFT

Learning to Reason with Insight for Informal Theorem Proving

arXiv:2604.16278v2 Announce Type: replace Abstract: Although most of the automated theorem-proving approaches depend on formal proof systems, informal theorem proving can align better with large language models' (LLMs) strength in natural language processing. In this work, we identify a primary bottleneck in informal theorem proving as a lack of insight, namely the difficulty of recognizing the core techniques required to solve complex problems.