CLIP-ADA: CLIP-Guided Artifact-Invariant Generalizable Synthetic Image Detection

This research paper presents CLIP-ADA, a method for detecting synthetic images (fake images created by AI generators) that works better across different types of generators and artifacts. The method analyzes how CLIP (a vision-language model that understands both images and text) processes images at different levels, then uses this understanding to train detectors that rely less on specific artifact patterns and more on general forensic features, achieving over 6% better accuracy on unseen synthetic images.