FakeVLM-R1: Internalizing Physical Laws via CoT for Synthetic Image Detection

ArXi:2605.30062v1 Announce Type: new The development of generative artificial intelligence technologies has propelled the visual realism of synthetic images to an unprecedented level. Although current interpretable detection methods based on Large Multimodal Models (LMMs) have made certain progress, they still rely on imitation learning derived from massive volumes of forged data. Consequently, they lack genuine causal reasoning capabilities and are prone to explanatory hallucinations.