Adaptive Memory Admission Control for LLM Agents

Researchers introduce Adaptive Memory Admission Control (A-MAC), a framework improving how LLM-based agents manage long-term memory. Current systems struggle with storing hallucinations or outdated information. A-MAC treats memory admission as a structured decision problem, evaluating five factors: future utility, factual reliability, semantic novelty, temporal relevance, and content type.