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New MeanFlow technique stabilizes large diffusion model distillation

作者 PulseAugur 编辑部 · [2 个来源] ·

Researchers have developed a new framework to stabilize and enhance MeanFlow, a technique used for distilling large-scale diffusion models. The method introduces a warm-up phase with a discrete solution before switching to the differential solution for refinement. Additionally, it incorporates trajectory distribution alignment to mitigate "mean-seeking bias" during few-step inference. This approach has demonstrated superior performance when applied to models like FLUX.1-dev and the 80B-parameter HunyuanImage 3.0. AI

影响 Enhances distillation efficiency for large diffusion models, potentially speeding up inference and deployment.

排序理由 Publication of an academic paper detailing a new method for improving diffusion model distillation.

在 Hugging Face Daily Papers 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

New MeanFlow technique stabilizes large diffusion model distillation

报道来源 [2]

  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    Stabilizing, Scaling & Enhancing MeanFlow for Large-scale Diffusion Distillation

    Diffusion models exhibit remarkable generative capability, but their high latency limits practical deployment. Many studies have attempted to reduce sampling steps to accelerate inference. Among them, MeanFlow has attracted considerable attention due to its concise formulation an…

  2. arXiv cs.CV TIER_1 English(EN) · Nannan Wang ·

    Stabilizing, Scaling & Enhancing MeanFlow for Large-scale Diffusion Distillation

    Diffusion models exhibit remarkable generative capability, but their high latency limits practical deployment. Many studies have attempted to reduce sampling steps to accelerate inference. Among them, MeanFlow has attracted considerable attention due to its concise formulation an…

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