AI RESEARCH
MetaMem: Evolving Meta-Memory for Knowledge Utilization through Self-Reflective Symbolic Optimization
arXiv CS.CL
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ArXi:2602.11182v2 Announce Type: replace Existing memory systems enable Large Language Models (LLMs) to long-horizon human-LLM interactions by persisting historical interactions beyond limited context windows. However, while recent approaches have succeeded in constructing effective memories, they often disrupt the inherent logical and temporal relationships within interaction sessions, resulting in fragmented memory units and degraded reasoning performance.