Deepfake Detection that Generalizes Across Benchmarks

ArXi:2508.06248v4 Announce Type: replace The generalization of deepfake detectors to unseen manipulation techniques remains a challenge for practical deployment. Although many approaches adapt foundation models by We conducted an extensive evaluation on 14 benchmark datasets spanning from 2019 to 2025. The proposed method achieves state-of-the-art performance, outperforming complex, recent approaches in average cross-dataset AUROC. Our analysis yields two primary findings for the field: 1