AINeutralarXiv – CS AI · May 96/10
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Channel-Level Semantic Perturbations: Unlearnable Examples for Diverse Training Paradigms
Researchers have developed a new technique called Shallow Semantic Camouflage (SSC) to protect personal data from unauthorized use in AI model training. The work addresses a critical gap where existing data protection methods fail under modern pretraining-finetuning paradigms, demonstrating that frozen pretrained weights significantly weaken previous unlearnable example approaches.