A Unified Prompt for Enhancing Heterogeneous Graph Pre-training via Edge-based Message Passing
Fengyu Yan, Xiaobao Wang, Qian-Xi Tang et al.
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Preprint
Jul 2026
AgentGFM: A Graph Foundation Model with Node-Agent Information-Flow Control
This work proposes AgentGFM, in which all node agents follow a shared end-to-end trainable policy rather than using independent models, and describes this capability as information-flow control, which is inspired by recent advances in agent technology.
Jingbo Cui, Jitao Zhao, Di Jin et al.
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