ActMem: Bridging the Gap Between Memory Retrieval and Reasoning in LLM Agents (opens in new tab)

arXiv:2603.00026v1 Announce Type: cross Abstract: Effective memory management is essential for large language model (LLM) agents handling long-term interactions. Current memory frameworks typically treat agents as passive "recorders" and retrieve information without understanding its deeper implications. They may fail in scenarios requiring conflict detection and complex decision-making. To bridge this critical gap, we propose a novel actionable memory framework called ActMem that integrates...