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IEEE/ICACT20260070 Slide.12        [Big Slide]	Oral Presentation
	For the detection module, the CLIP ViT-L/14 model functions as the feature extractor, with its pre-trained weights frozen to retain general semantic knowledge . Low-Rank Adaptation (LoRA) modules are inserted into the transformer blocks, specifically training only the rank-8 matrices . This enables fine-tuning using just 0.32% of the total parameters approximately 1.35 million out of 400 million . A contrastive loss function aligns the image and text features, followed by an MLP classifier to determine the authenticity of the image.

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