AI RESEARCH
BIAS-ID: A Framework for Analyzing Transformation Biases in AI-Generated Image Detectors
arXiv CS.CV
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ArXi:2605.31153v1 Announce Type: new Given the surge of harmful AI-generated imagery online, reliably distinguishing authentic images from generated ones has become an urgent research topic. While many proposed detection methods perform well under controlled settings, they often collapse when tested on real-world data. A potential root cause are subtle biases in the detectors'