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Department of Computer Science and Engineering
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Multilingual moral reasoning can be dramatically improved by grounding decisions in culturally specific contexts and theoretical frameworks, leading to significant performance gains.
By using text as an anchor, this model achieves state-of-the-art emotional mimicry intensity estimation, even when visual and acoustic data are noisy or missing.
A dual-branch Transformer with safe cross-attention overcomes missing visual cues in emotion recognition by dynamically relying on audio, achieving state-of-the-art results on Aff-Wild2.
