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Achieving intended outcomes in video generation while maintaining semantic relevance is more challenging than previously thought, with current models falling short.
Achieve superior video generation quality and temporal coherence without expensive retraining by intelligently scaling and steering diffusion models at test time.
Stop wasting compute on unreliable rollouts and easy frames: Stream-R1 adaptively focuses video diffusion distillation where it matters most, boosting quality without architectural changes or added inference cost.
