Revealing the Truth with ConLLM for Detecting Multi-Modal Deepfakes
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 investigation into the challenges of detecting deepfakes, with multiple competing theories on how to improve detection methods and notable unknowns regarding the effectiveness of new approaches like ConLLM.
The rapid rise of deepfake technology poses a severe threat to social and political stability by enabling hyper-realistic synthetic media capable of manipulating public perception. However, existing detection methods struggle with two core limitations: (1) modality fragmentation, which leads to poor generalization across diverse and adversarial deepfake modalities; and (2) shallow inter-modal reasoning, resulting in limited detection of fine-grained semantic inconsistencies. To address these,...