Explainable Deepfake Detection with RL Enhanced Self-Blended Images
How much verified proof exists for this claim
One strong evidence source: arxiv
How intriguing or unexplained this claim is
The claim involves an active area of research with ongoing investigations into the use of multimodal large language models for explainable deepfake detection, highlighting the challenges of dataset scarcity and the complexity of forgery attribution, which presents notable unknowns and competing theories.
Most prior deepfake detection methods lack explainable outputs. With the growing interest in multimodal large language models (MLLMs), researchers have started exploring their use in interpretable deepfake detection. However, a major obstacle in applying MLLMs to this task is the scarcity of high-quality datasets with detailed forgery attribution annotations, as textual annotation is both costly and challenging - particularly for high-fidelity forged images or videos. Moreover, multiple studi...