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Accelerating Video Diffusion via Training-Free Trajectory Routing
Video diffusion is computationally expensive, as it requires executing a large model across many denoising steps. Even with step-distillation, inference remains expensive because every distilled step still requires a costly model evaluation. We present TRACK: TRajectory-Aware Capacity routing via top-K selection, a heterogeneous denoising strategy that switches between compatible large and small models at selected steps, reducing the average cost per denoising evaluation. The switching steps are determined using a calibration process. TRACK first rolls out a reference trajectory with the large
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-24T16:39:47.000Z
First collected: 2026-09-25T06:12:46.948Z. This is not the publication date.