AI RESEARCH
HiGMem: A Hierarchical and LLM-Guided Memory System for Long-Term Conversational Agents
arXiv CS.CL
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ArXi:2604.18349v1 Announce Type: new Long-term conversational large language model (LLM) agents require memory systems that can recover relevant evidence from historical interactions without overwhelming the answer stage with irrelevant context. However, existing memory systems, including hierarchical ones, still often rely solely on vector similarity for retrieval.