Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All?

Feb-14-2026, 14:18:54 GMT–Neural Information Processing Systems

Notably, most real-world homophilic and heterophilic graphs are comprised of a mixture of nodes in both homophilic and heterophilic structural patterns, exhibiting a structural disparity.

data mining, machine learning, node, (21 more...)

Neural Information Processing Systems

Feb-14-2026, 14:18:54 GMT

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