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Open access Aug 2026

Generate and Filter: A GNN-Based Approach for Graph Anomaly Detection.

A novel framework, Generate and Filter graph learning for Graph Anomaly Detection (GFGAD), which generates a diverse set of synthetic anomalies with enriched feature and structural information to balance the data distribution and significantly outperforms state-of-the-art baselines.

Mengyu Li, Yonghao Liu, Ximing Li et al. · 0 citations