AI Research
Honest Fusion Evaluation for Cross-Domain Deepfake Detection: Leakage Audits and Tail Robustness
A study of fusion strategies, leakage audits, and robustness in cross-domain video detection
Cross-domain video deepfake detection increasingly uses frozen foundation-model experts, combined by calibrated score averaging, a per-video router picking one expert, or a learned head over concatenated features.
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ArXiv CS.CV
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2 min
ArXiv CS.CV
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Generated insight by OnAirToday AI
Comparing fusion strategies can clarify how frozen foundation-model experts contribute to cross-domain deepfake detection. Leakage audits and tail-robustness checks matter because evaluation must reveal whether performance generalizes beyond the data used to develop a detector.
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