Meta-Cognitive Memory Policy Optimization for Long-Horizon LLM Agents 事件

Meta-Cognitive Memory Policy Optimization for Long-Horizon LLM Agents arXiv:2605.30159v1 Announce Type: new Abstract: Memory-augmented LLM agents tackle complex long-horizon tasks by recursively summarizing interaction trajectories into compact memory. However, existing approaches typically train these memory policies using outcome-based reinforcement learning, failing to localize where intermediate memory quality degrades. As interactions unfold, ambiguous recursive summaries progressively dis