Solving the Granularity Mismatch: Hierarchical Preference Learning for Long-Horizon LLM Agents
Large Language Models (LLMs) as autonomous agents are increasingly tasked with solving complex, long-horizon problems. Aligning these agents via preference-based methods like Direct Preference Optimization (DPO) is a promising direction, yet it faces a critical granularity mismatch. Trajectory-lev…