AINeutralarXiv – CS AI · 9h ago6/10
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Beyond Soft Masks: Hard-Perturbation Mixup Explainer for Robust GNN Explainability
Researchers propose HPME, a novel framework for explaining Graph Neural Network decisions using hard-perturbation mixup strategies instead of soft masks. The method addresses out-of-distribution issues in GNN explainability by extracting discrete subgraphs and employing structure-level replacement, achieving improved explanation fidelity across synthetic and real-world datasets.