Zhibiao Guo

DIFT: Protecting Contrastive Learning Against Data Poisoning Backdoor Attacks

Contrastive learning (CL) is a popular learning paradigm that excels in extracting meaningful representations from unlabeled data. Recent studies have shown that CL is highly vulnerable to backdoor attacks. Current defenses against backdoor attacks in CL are primarily reactive and post-training. Tha