A joint text-graph contrastive learning framework detects anomalies in text-attributed graphs and outperforms eleven baselines across eight new datasets.
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Text-Attributed Graph Anomaly Detection via Multi-Scale Cross- and Uni-Modal Contrastive Learning
A joint text-graph contrastive learning framework detects anomalies in text-attributed graphs and outperforms eleven baselines across eight new datasets.