SAOT applies structure-aware optimal transport to capture global inter-node correspondences and uses cross-task distillation to retain prior structural knowledge, yielding accuracy gains of up to 15% on Products-CL in class-incremental settings.
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SAOT: Self-Supervised Continual Graph Learning with Structure-Aware Optimal Transport
SAOT applies structure-aware optimal transport to capture global inter-node correspondences and uses cross-task distillation to retain prior structural knowledge, yielding accuracy gains of up to 15% on Products-CL in class-incremental settings.