LaDA-Band applies discrete masked diffusion with dual-track conditioning and progressive training to generate vocal-to-accompaniment tracks that improve acoustic authenticity, global coherence, and dynamic orchestration over prior baselines.
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PRISM learns shared sentiment prototypes to enable structured cross-modal comparison and dynamic modality reweighting in multimodal sentiment analysis, outperforming baselines on three benchmark datasets.
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LaDA-Band: Language Diffusion Models for Vocal-to-Accompaniment Generation
LaDA-Band applies discrete masked diffusion with dual-track conditioning and progressive training to generate vocal-to-accompaniment tracks that improve acoustic authenticity, global coherence, and dynamic orchestration over prior baselines.