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cs.CV2024
Defending Multimodal Backdoored Models by Repulsive Visual Prompt Tuning
Zhifang Zhang, Shuo He, Haobo Wang +2
Multimodal contrastive learning models (e.g., CLIP) can learn high-quality representations from large-scale image-text datasets, while they exhibit significant vulnerabilities to b…
cs.LG2024★ 2 cited
Backdoor Secrets Unveiled: Identifying Backdoor Data with Optimized Scaled Prediction Consistency
Soumyadeep Pal, Yuguang Yao, Ren Wang +2
Modern machine learning (ML) systems demand substantial training data, often resorting to external sources. Nevertheless, this practice renders them vulnerable to backdoor poisonin…