s. Retrofitting the open-source Wan-2.1 model speeds up attention
time by 6$\times$ and lowers end-to-end generation time from 31s to 18s with
comparable quality. These results establish trainable sparse attention as a
practical alternative to full attention and a key enabler for further scaling
of video diffusion models.</p>
            
            <p class="paper-tldr"><strong>TLDR</strong>: The paper introduces VSA, a trainable sparse attention mechanism for video diffusion transformers that significant