VAD
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VAD-GS: Visibility-Aware Densification for 3D Gaussian Splatting in Dynamic Urban Scenes
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An Analysis Focused on Womens Safety: Can VAD Models Be Enhanced by a Multi-modal Dataset?
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LLM-Enhanced Dialogue Management for Full-Duplex Spoken Dialogue Systems
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Ousiometrics: The essence of meaning aligns with a power-danger-structure framework instead of valence-arousal-dominance
arXiv:2110.06847v3 Announce Type: replace-cross Abstract: From work emerging through the middle of the 20th century, the essence of meaning has become widely accepted as being described by the three orthogonal dimensions of valence, arousal, and dominance (VAD). These essential dimensions have become the cornerstone of sentiment analysis across many fields.
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TRADE: Transducer-Augmented Decoder for Speech LLM
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Towards Accurate Emotion-Attributed Video Captioning via Fine-grained Emotion-Cause Pair Extraction
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