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CUNO: Curriculum and Preference Optimization for Stable Graph Unlearning under Mass Deletion
Graph unlearning removes the influence of designated training data from a trained graph model without retraining from scratch. However, existing methods suffer a sharp drop in model utility under large deletion ratios (mass deletion), a phenomenon we refer to as catastrophic unlearning. We find that
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