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cs.LG2026
Rethinking Molecular Graph Backdoors under Chemistry-aware Admission
Thinh T. H. Nguyen, Sze Jue Yang, Khoa D. Doan +2
Backdoor attacks on molecular graph neural networks (GNNs) are typically evaluated as abstract graph edits, but real molecular learning pipelines do not train on arbitrary graphs.…
cs.LG2025
FLAT: Revealing Hidden Latent-Conditioned Backdoor Failures in Federated Learning
Tuan Nguyen, Sze Jue Yang, Khoa D. Doan +2
Horizontal federated learning (HFL) backdoor audits often summarize model behavior through clean accuracy (CA), mean attack success rate (ASR), or a single known-trigger test. Such…