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Meixia He

2 accepted papers

2026

Transferable Hypergraph Attack via Injecting Nodes into Pivotal Hyperedges

AAAI 2026technical

Recent studies have demonstrated that hypergraph neural networks (HGNNs) are susceptible to adversarial attacks. However, existing methods rely on the specific information mechanisms of target HGNNs, overlooking the common vulnerability caused by the significant differences in hyperedge pivotality a

Cited by 0SourcePDFScholar
2025

Hypergraph Attacks via Injecting Homogeneous Nodes into Elite Hyperedges

AAAI 2025technical

Recent studies have shown that Hypergraph Neural Networks (HGNNs) are vulnerable to adversarial attacks. Existing approaches focus on hypergraph modification attacks guided by gradients, overlooking node spanning in the hypergraph and the group identity of hyperedges, thereby resulting in limited at…

Cited by 2SourcePDFScholar