研究人员开发了一个新框架，用于稳定和增强MeanFlow，这是一种用于蒸馏大型扩散模型的技术。该方法引入了一个具有离散解的热身阶段，然后切换到微分解进行优化。此外，它还结合了轨迹分布对齐，以减轻少步推理过程中的“均值趋向偏差”。这种方法在应用于FLUX.1-dev和800亿参数HunyuanImage 3.0等模型时，表现出了卓越的性能。 AI
影响 提高了大型扩散模型的蒸馏效率，可能加快推理和部署速度。
排序理由 发表了一篇学术论文，详细介绍了一种改进扩散模型蒸馏的新方法。
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 →
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…
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…