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arXiv AI By Jian Zhong, Zeyu Liu, Pingchuan Cao, Rongduo Han, Shunye Tang, Guohuan Xie, Mingyuan Qin, Ran Ji, Xiao Liang, Wei Wang, Haining Zhang

PreCoMem: Predictive Cognitive Memory for Self-Evolving Long-Term Dialogue Agents

Read the original on arXiv AI →

PreCoMem introduces a memory consolidation framework for long‑horizon dialogue agents, inspired by predictive coding. It represents user memory as confidence‑weighted beliefs and uses an Effective Surprisal signal to decide whether to maintain, profile, or correct each belief. Experiments on LoCoMo, LongMemEval‑S, PersonaMem‑v2, and the new DiMoBench demonstrate state‑of‑the‑art accuracy and robust adaptation to non‑stationary belief drift without over‑reacting to noise.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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