Memory is Reconstructed, Not Retrieved: Graph Memory for LLM Agents 事件

Memory is Reconstructed, Not Retrieved: Graph Memory for LLM Agents arXiv:2606.06036v1 Announce Type: new Abstract: Despite recent progress, LLM agents still struggle with reasoning over long interaction histories. While current memory-augmented agents rely on a static retrieve-then-reason paradigm, this rigid pipeline design prevents them from dynamically adapting memory access to intermediate evidence discovered during inference. To bridge this gap, we propose MRAgent, a framework that combin