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This work proposes MemDream, a framework that enables self-probing memory evolution for LLM agents and periodically enters offline dream cycles where three specialized agents collaboratively probe, diagnose, and repair the memory graph before failures occur.
A novel method is proposed, Evidence-Aligned Entity Verification (EAEV), which detects entity-level hallucinations by leveraging RAG to align generated entities with retrieved evidence contexts and introduces counterfactual stability analysis to ensure robust alignments under evidence perturbations.
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