4 papers
Order-based Rehearsal Learning
Yu-Xuan Tao, Tian-Zuo Wang, Zhi-Hua Zhou
When a machine learning (ML) model forecasts an undesired event, one often seeks a decision to avoid it, known as the avoiding undesired future (AUF) problem. Many rehearsal learni…
Detecting Deepfakes via Hamiltonian Dynamics
Harry Cheng, Ming-Hui Liu, Tianyi Wang +3
Driven by the rapid development of generative AI models, deepfake detectors are compelled to undergo periodic recalibration to capture newly developed synthetic artifacts. To break…
FractalForensics: Proactive Deepfake Detection and Localization via Fractal Watermarks
Tianyi Wang, Harry Cheng, Ming-Hui Liu +1
Proactive Deepfake detection via robust watermarks has seen interest ever since passive Deepfake detectors encountered challenges in identifying high-quality synthetic images. Howe…
Fair Deepfake Detectors Can Generalize
Harry Cheng, Ming-Hui Liu, Yangyang Guo +3
Deepfake detection models face two critical challenges: generalization to unseen manipulations and demographic fairness among population groups. However, existing approaches often…