AutoMEM Accepted at AACL 2026

Our collaborative paper Exploring Cross-Scenario Generality of Agentic Memory Systems: Diagnostics and a Strong Baseline, by Zhikai Chen, Jialiang Gu, Junyu Yin, Xianxuan Long, Shenglai Zeng, Xiaoze Liu, Kai Guo, Keren Zhou, and Jiliang Tang, has been accepted at AACL-IJCNLP 2026. The paper evaluates agent memory systems across different scenarios and introduces AutoMEM, a baseline that lets agents manage memory through tools. Congratulations to all the authors!