When Evidence Shapes Collaboration: Knowledge-Conditioned Topology Generation for Multi-Agent Systems
This work proposes K-GAT (Knowledge-Guided Agent Topology Generator), a neuro-symbolic framework that formulates collaboration topology design as a knowledge-conditioned structure learning problem, integrating external evidence directly into autoregressive graph generation.
Yang-Xiao Jiang, Jia-Run Fan, Ming-Cong Xu et al.
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