Yuxiang Zhang

LoSplit: Loss-Guided Dynamic Split for Training-Time Defense Against Graph Backdoor Attacks

LoSplit is proposed, the first training-time defense framework in graph that leverages this early-stage loss drift to accurately split target nodes, and dynamically selects epochs with maximal loss divergence, clusters target nodes via Gaussian Mixture Models, and applies a Decoupling-Forgetting strategy to break the association between target nodes and malicious label.