DGS-Net decomposes gradients into harmful and beneficial directions, projects task updates onto the orthogonal complement of harmful ones, and aligns with distilled signals from frozen CLIP to fine-tune for AI-image detection while preserving priors.
CNN-Spot employs convolutional neural networks to detect synthetic content by analyzing common spatial artifacts in AI-generated images
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DGS-Net: Distillation-Guided Gradient Surgery for CLIP Fine-Tuning in AI-Generated Image Detection
DGS-Net decomposes gradients into harmful and beneficial directions, projects task updates onto the orthogonal complement of harmful ones, and aligns with distilled signals from frozen CLIP to fine-tune for AI-image detection while preserving priors.