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Glance Forcing Enhances Bidirectional Diffusion Autoregression

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Glance Forcing is a new technique that enhances the efficiency of bidirectional diffusion autoregression by decomposing denoising trajectories into two complementary experts. This method has significantly improved video generation efficiency and reduced training costs. It has lowered the cost of trajectory supervision to a single sample, maintaining high quality while reducing the trajectory collection cost from thousands of GPU hours to approximately one A100-GPU hour.

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最新进展10月14日 04:00

Glance Forcing has been introduced as a method to improve the efficiency of bidirectional diffusion autoregression, reducing training costs and increasing video generation efficiency.

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10月14日

04:00
Hugging Face Daily Papers
Glance Forcing：通过阶段特定目标引导的专家提高双向扩散自回归的效率
Glance Forcing 通过将去噪轨迹分解为两个互补的专家，显著提高了视频生成效率，并降低了训练成本。该方法将轨迹监督降低到单个样本，在保持高质量的同时，将轨迹收集成本从数千个 GPU 小时降低到大约一个 A100-GPU 小时。

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