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Evidence Subspace Projection reveals how different factors influence deepfake detection decisions, providing a clearer understanding of model behavior in self-supervised learning.
The best deepfake audio detectors are surprisingly biased by audio quality, speaker gender, and language, undermining their real-world reliability.
Conflicting labels on codec-resynthesized audio can significantly impact audio deepfake detection, highlighting a critical challenge in dataset creation and model training.
