Hierarchical Graph Memory for LLM Agents with Path-level Localization and Rewrite
Agents for long term reasoning require a memory that can be efficiently and effectively updated over time, as new facts and external feedback continue to arrive. Recently, graph memory has been adopted to offer structural organization for multi-hop retrieval and reasoning. However, existing methods store all memories in a flat graph, and accumulated historical memories can introduce irrelevant…
We haven't written up this one. arXiv cs.AI has the full story — the link below goes straight to it.
