MICA: Multi-granularity Intertemporal Credit Assignment for Long-Horizon Emotional Support Dialogue

Reinforcement learning (RL) for large language models (LLMs) has shown strong performance in single-turn tasks, but extending it to multi-turn interaction remains challenging due to sparse rewards and poor per-turn credit assignment. In emotional support dialogues, responses shape future user states