On the optimization dynamics of RLVR: Gradient gap and step size thresholds

arXiv:2510.08539v4 Announce Type: replace-cross Abstract: Reinforcement Learning with Verifiable Rewards (RLVR), which uses simple binary feedback to post-train large language models, has found significant empirical success. However, a principled understanding of why it works is lacking. This paper...