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OCSVM-based drift detection achieves comparable accuracy to constant retraining while drastically improving training efficiency in malware classification.
AI-art detectors misclassify up to 40% of images from new generative models, revealing a dangerous vulnerability in copyright and authenticity verification.
Accuracy and explanation faithfulness in malware detection are at odds, with the most interpretable models yielding only mid-tier performance.
