by an average of 36.7% at the same or
higher compression ratios. When a video generation model is trained using
RefTok's latents on the BAIR Robot Pushing task, the generations not only
outperform MAGVIT-B but the larger MAGVIT-L, which has 4x more parameters,
across all generation metrics by an average of 27.9%.</p>
            
            <p class="paper-tldr"><strong>TLDR</strong>: The paper introduces RefTok, a novel reference-based tokenization method for video generation that captures temporal dynami