Beyond Precision: Why Training-Inference Mismatch is an Optimization Problem and How Simple LR Scheduling Fixes It

Corresponding Author: Yingru Li Co-First Authors: Yaxiang Zhang and Yingru Li TL;DR The Problem: Reinforcement Learning (RL) training for LLMs is notoriously unstable. While recent studies attribute this to &ldquo;training-inference mismatch&rdquo; (caused by hybrid engines), standard fixes like Importance Sampling might fail during longer training runs. The Insight: We analyze this instability…