Multi-Agent Agentic Graph Learning via Structural Signatures
A multi-agent agentic graph learning framework that partitions the graph into communities and assigns an independent agent to each community for region-specific specialization and shows that MAAGL outperforms SOTA AGL methods.
Liang Qu, Jian-Xin Li, Hua Wang
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