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DeBERTa-ConPara: Attack-Aware and Deployment-Realistic Detection of AI-Generated Text
Robust detection of AI-generated text under deployment conditions is challenging: distribution shifts across domains and generators, adversarial perturbations of the input surface, and the absence of target-domain labels for threshold calibration all degrade detectors that perform well in-domain. We
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