arXiv:2606.20283v2 Announce Type: replace-cross Abstract: Graph neural networks (GNNs) excel at aggregating neighbor information for classification, yet their performance is hindered by graph structural entanglement, where spurious correlations from semantically irrelevant neighbors contaminate node embeddings. This challenge is most acute for nodes near class boundaries…
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Source: cs.AI updates on arXiv.org
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