arXiv AI October 28, 2026 By Jinyang Li, Zichuan Fu, Xian Wu, Wenlin Zhang, Yimin Deng, Kaifeng Guo, Guojing Li, Junjia QI, Xiangyu Zhao

Proactive Memory for Event-Driven LLM Agents

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Proactive Memory for Event-Driven LLM Agents introduces ProactMem, a system that organizes an agent’s history into recent events, temporal trajectories, and behavioral regularities. It validates trajectory facts against source events and assesses regularities through historical replay before matching them to current conditions. The authors also present ProactiveStream, a longitudinal benchmark with three application scopes, and report that ProactMem achieves an overall F1 of 52.6%, a 21.4% relative improvement over the strongest of five external baselines.

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