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IEEE/ICACT20260070 Slide.05        [Big Slide]	Oral Presentation
	The research builds upon the CLIP architecture, a multimodal model pre-trained on 400 million image-text pairs and known for strong zero-shot capabilities . While existing methods like "Linear Probing" or "Adapter Networks" utilize CLIP for detection, these approaches typically focus solely on binary classification- determining if an image is real or fake without providing an explanation . This work addresses that gap by enhancing CLIPs semantic understanding through generated descriptions and adding an interpretability layer to identify specific generation traces .

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