Deepfake Attribution with Asymmetric Learning for Open-World Detection

This ArXiv paper explores deepfake detection, a crucial area of research given the increasing sophistication of AI-generated content. The application of confidence-aware asymmetric learning represents a novel approach to addressing the challenges of open-world deepfake attribution.