GAAMA constructs a four-node-type knowledge graph with concept-mediated edges and Personalized PageRank retrieval to improve multi-session agent memory, reporting 79.1% mean reward on LoCoMo-10 (+4.2 pp over tuned RAG) and gains on MemoryArena tasks that grow with dialogue length.
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GAAMA: Graph Augmented Associative Memory for Agents
GAAMA constructs a four-node-type knowledge graph with concept-mediated edges and Personalized PageRank retrieval to improve multi-session agent memory, reporting 79.1% mean reward on LoCoMo-10 (+4.2 pp over tuned RAG) and gains on MemoryArena tasks that grow with dialogue length.