SGR turns adversarial shortcuts into teachers, isolating invariant subgraph rationales and delivering the first XGL framework ...
Abstract: Graph neural networks (GNNs), a class of deep learning models designed for performing information interaction on non-Euclidean graph data, have been successfully applied to node ...
Abstract: Heterogeneous Graph Neural Networks (HGNNs) have attracted significant research attention in recent years due to their ability to capture complex interactions among various node types in ...
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