papersSEP 10 04:00 UTC
EviMem proposes evidence-gap-driven iterative retrieval for long-term conversational memory
Researchers present EviMem, a retrieval method for long-term conversational memory that identifies gaps in the evidence gathered so far and iteratively fetches additional material across past sessions. The approach targets temporal and multi-hop questions where a single retrieval pass typically fails to locate relevant information. The paper is available as a revised version (v2) on arXiv.