Context-Aware Subgraph Explanations for Multi-Task GNNs
The proposed CAMIE, a Context-Aware Motif Importance Explainer designed for multi-task molecular classification, leverages a Knowledge Distillation-inspired pseudo target to effectively distill assay-specific motif-removal responses, transferring explanatory patterns across tasks without requiring ground-truth labels.
Yejin Yoon, Jaesung Lim, Jinhee Choi et al.
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