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Learning Continuous Source Responses For Generalizable AI-Generated Image Detection

arXiv · AI, language, vision and robotics · article · Sep 13, 2026 · UTC

Advances in image generation have made synthetic images increasingly difficult to distinguish from real photographs, raising concerns about the trustworthiness of visual media. Existing AI-generated image detectors often perform well on in-domain data, but their robustness and cross-generator generalization remain limited. These limitations are commonly attributed to overfitting to shortcut cues. Although many methods seek to suppress shortcut learning, most retain binary classification as the training task without reconsidering how the task itself shapes the learned representations. We introd

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Evidence & attribution

First collected: 2026-09-20T12:41:04.663Z. This is not the publication date.