A majority vote of large vision-language models is claimed to detect backdoor triggers in face images, with calibrated noise correcting poisoned samples at 100% accuracy.
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From Detection to Correction: Backdoor-Resilient Face Recognition via Vision-Language Trigger Detection and Noise-Based Neutralization
A majority vote of large vision-language models is claimed to detect backdoor triggers in face images, with calibrated noise correcting poisoned samples at 100% accuracy.