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Achieving a 20.7% reduction in compute while enhancing anti-spoofing robustness could redefine deployment strategies in self-supervised learning.
You can halve the size of your deepfake detection ensemble without sacrificing accuracy by using evolutionary multi-objective optimization to select and weight individual detectors.
