RREDCoT: Segment-Level Reward Redistribution for Reasoning Models

arXiv 2606.06475·medium signal

RREDCoT improves RL fine-tuning of reasoning models by redistributing reward at the segment level of a chain-of-thought rather than only at the final answer, giving denser credit assignment across reasoning steps. This addresses the sparse-reward problem that limits RL-trained reasoners. Relevant for teams training their own reasoning models.