Learning with Blacklists on Graphs via Prototype-Guided Dual-Frequency Filtering
Graph-based fraud detection plays a critical role in identifying anomalous accounts and preventing financial losses in real-world systems, where graphs often contain millions of nodes but only a limited number of blacklist labels are available. Existing graph neural network approaches typically rely on full-graph messa...