SynCred-Bench shows that 15 MLLMs reach only 10.5% TPR, open-source detectors under 5%, commercial APIs 57.6%, and humans 63% TPR at 5% FPR when identifying AI-generated images with synthetic credibility.
International Journal of Computer Vision , year =
2 Pith papers cite this work. Polarity classification is still indexing.
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Introduces Ex-HateMM and Ex-ImpliHateVid datasets and the IARE framework using multimodal CoT and DPO to achieve explainable hateful video detection with claimed SOTA performance.
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SynCred-Bench: Benchmarking Synthetic Credibility in AI-Generated Visual Misinformation
SynCred-Bench shows that 15 MLLMs reach only 10.5% TPR, open-source detectors under 5%, commercial APIs 57.6%, and humans 63% TPR at 5% FPR when identifying AI-generated images with synthetic credibility.
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Decoding Multimodal Cues: Unveiling the Implicit Meaning Behind Hateful Videos
Introduces Ex-HateMM and Ex-ImpliHateVid datasets and the IARE framework using multimodal CoT and DPO to achieve explainable hateful video detection with claimed SOTA performance.