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RACE: Relation-Level Counterfactual Explanations for Heterogeneous Graph Neural Networks
Counterfactual explanations of graph neural networks identify edge deletions that flip a prediction. On heterogeneous graphs, however, existing methods first collapse the graph into untyped edges, so they cannot answer the question a domain expert actually asks: which relation type drives this predi
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