SAGE: A Self-Evolving Agentic Graph-Memory Engine for Structure-Aware Associative Memory
Long-term memory is becoming a central bottleneck for language agents. Exsting RAG and GraphRAG systems largely treat memory graphs as static retrieval middleware, which limits their ability to recover complete evidence chains from partial cues, exploit reusable graph-structrual roles, and improve the memory itself through downstream feedback. We introduce SAGE, a Self-evolving Agentic Graph-memory Engine that models graph memory as a dynamic long-term memory substrate. SAGE couples two roles: a memory writer that incrementally constucts structured graph memory from interaction histories, and a Graph Foundation Model-based memory reader to perform retrieval and provide feedback to the mem...
| Authors | Juntong Wang, Haoyue Zhao, guanghui Pan et al. |
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| Primary category | cs.AI |
| Published | 12 May 2026 |
| Last updated at source | 22 September 2026 |
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