AI RESEARCH
VIGIL: Part-Grounded Structured Reasoning for Generalizable Deepfake Detection
arXiv CS.CV
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ArXi:2603.21526v1 Announce Type: new Multimodal large language models (MLLMs) offer a promising path toward interpretable deepfake detection by generating textual explanations. However, the reasoning process of current MLLM-based methods combines evidence generation and manipulation localization into a unified step. This combination blurs the boundary between faithful observations and hallucinated explanations, leading to unreliable