Preprint Open access
SHARPO: Segment-Level Credit Assignment for Agentic Reinforcement Learning
Agentic reinforcement learning (RL) trains a large language model (LLM) to act over long, multi-step interactions. However, a single localized error can cause task failure, while trajectory-level rewards provide limited guidance for assigning credit to individual decisions. To address this limitation, we introduce Segm …