AINeutralarXiv – CS AI · Jun 196/10
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Hybrid Diffusion Transformer for Instruction-Guided Audio Editing via Rectified Flow
Researchers propose a hybrid diffusion transformer architecture for audio editing that uses a two-stage approach with rectified flow matching to balance performance and computational efficiency. The method addresses limitations of existing approaches by combining joint attention for semantic alignment at low resolution with alternating attention mechanisms at high resolution, enabling more accurate instruction-guided audio editing with reduced computational complexity.