AIBullisharXiv – CS AI · 10h ago6/10
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Learning What Not to Forget: Long-Horizon Agent Memory from a Few Kilobytes of Learning
Researchers present LRE (Learned Relevance Eviction), a lightweight memory management system for long-running language model agents that intelligently decides which historical information to retain when context windows fill up. The approach uses a small, CPU-based scorer to identify critical details like access tokens and task-relevant information, achieving comparable accuracy to keeping full history while reducing peak context size by up to 52% and requiring significantly fewer computational calls.