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This paper proposes Emo-Boost, a multimodal deepfake detection framework that leverages emotion cues (audio-visual emotion recognition) as high-level semantic signals to improve generalization to unseen manipulation types, achieving a 2.1% average AUC improvement on the FakeAVCeleb dataset.