FDQ improves stability in multimodal graph unlearning by using feature-dimension aware quantile selection to protect sensitive high-dimensional layers while preserving utility and enabling effective forgetting.
Graph learn- ing for anomaly analytics: Algorithms, applications, and challenges,
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Stable Multimodal Graph Unlearning via Feature-Dimension Aware Quantile Selection
FDQ improves stability in multimodal graph unlearning by using feature-dimension aware quantile selection to protect sensitive high-dimensional layers while preserving utility and enabling effective forgetting.