AI RESEARCH
GAM: Hierarchical Graph-based Agentic Memory for LLM Agents
arXiv CS.AI
•
ArXi:2604.12285v1 Announce Type: new To sustain coherent long-term interactions, Large Language Model (LLM) agents must navigate the tension between acquiring new information and retaining prior knowledge. Current unified stream-based memory systems facilitate context updates but remain vulnerable to interference from transient noise. Conversely, discrete structured memory architectures provide robust knowledge retention but often struggle to adapt to evolving narratives.