SAGE is a self-evolving agentic graph-memory engine that dynamically constructs and refines structured memory graphs via writer-reader feedback, yielding performance gains on multi-hop QA, open-domain retrieval, and long-term agent benchmarks.
arXiv preprint arXiv:2302.12449 , year=
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PLACE is a prompt-augmented graph framework for attributed community search that integrates learnable tokens with GNNs via alternating training and divide-and-conquer scaling, achieving 22% higher average F1 scores than prior methods on nine real-world graphs.
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SAGE: A Self-Evolving Agentic Graph-Memory Engine for Structure-Aware Associative Memory
SAGE is a self-evolving agentic graph-memory engine that dynamically constructs and refines structured memory graphs via writer-reader feedback, yielding performance gains on multi-hop QA, open-domain retrieval, and long-term agent benchmarks.
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PLACE: Prompt Learning for Attributed Community Search in Large Graphs
PLACE is a prompt-augmented graph framework for attributed community search that integrates learnable tokens with GNNs via alternating training and divide-and-conquer scaling, achieving 22% higher average F1 scores than prior methods on nine real-world graphs.