2026
Understanding Reasoning Collapse in LLM Agent Reinforcement Learning
ICML 2026oral
In closed-loop multi-turn agent reinforcement learning, LLM agents exhibit reasoning collapse, where reasoning shift toward generic templates, weakly coupled to the inputs. We firstly identify that such collapse is easy to miss with entropy or surface diversity metrics since reasoning text still var…