Most graph neural network defenses improve explanation sparsity and stability in this benchmark, while the consistency and fidelity metrics largely saturate and stop being informative.
A comprehensive survey on trustworthy graph neural networks: Privacy, robustness, fairness, and explainability
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Robustness questions the interpretability of graph neural networks: what to do?
Most graph neural network defenses improve explanation sparsity and stability in this benchmark, while the consistency and fidelity metrics largely saturate and stop being informative.