T2SPO: Trajectory-to-Step Policy Optimization for Agentic Reinforcement Learning.

arXiv:2610.00388v1 Announce Type: cross Abstract: Reinforcement learning enables large language model (LLM) agents to learn multi-step behaviors through interaction with their environments. However, rewards in many interactive tasks reflect only the final outc