Papers
1–4 of 4Context and Transcripts Improve Detection of Deepfake Audios of Public Figures
Humans use context to assess the veracity of information. However, current audio deepfake detectors only analyze the audio file without considering either context or transcripts. We create and analyze...
EvolveReason: Self-Evolving Reasoning Paradigm for Explainable Deepfake Facial Image Identification
With the rapid advancement of AIGC technology, developing identification methods to address the security challenges posed by deepfakes has become urgent. Face forgery identification techniques can be ...
X-AVDT: Audio-Visual Cross-Attention for Robust Deepfake Detection
The surge of highly realistic synthetic videos produced by contemporary generative systems has significantly increased the risk of malicious use, challenging both humans and existing detectors. Agains...
Naïve Exposure of Generative AI Capabilities Undermines Deepfake Detection
Generative AI systems increasingly expose powerful reasoning and image refinement capabilities through user-facing chatbot interfaces. In this work, we show that the naïve exposure of such capabilitie...