CAMERA is an ego-decoupled mixture-of-experts model with context-informed gating and one-class objectives for unsupervised fraud detection in text-attributed graphs facing semantic camouflage.
Text-attributed graph anomaly detection via multi-scale cross-and uni-modal contrastive learning.arXiv preprint arXiv:2508.00513
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N2NSC framework detects anomalies in text-attributed graphs by enforcing node-to-neighborhood semantic consistency via two complementary fusion paths that align textual semantics with topology.
citing papers explorer
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CAMERA: Adapting to Semantic Camouflage in Unsupervised Text-Attributed Graph Fraud Detection
CAMERA is an ego-decoupled mixture-of-experts model with context-informed gating and one-class objectives for unsupervised fraud detection in text-attributed graphs facing semantic camouflage.
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Node-to-Neighborhood Semantic Consistency: Text-Topology Alignment for TAGs Anomaly Detection
N2NSC framework detects anomalies in text-attributed graphs by enforcing node-to-neighborhood semantic consistency via two complementary fusion paths that align textual semantics with topology.