Unverified50% confidenceFactExact time
CFG is a core hyperparameter in diffusion models, rooted in a 2022 research finding, and works by enhancing responsiveness to text descriptions through a weighted mixture of the predictions from the conditional and unconditional denoising paths.
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9/20/2026
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Unverified文本引导的去噪过程本质上是Classifier-Free Guidance（CFG）机制在起作用，模型同时预测有条件和无条件的噪声估计，两者差值被放大后引导生成方向72% similarUnverifiedCFG performs conditional and unconditional predictions separately during inference and interpolates and amplifies them via the formula output = uncond + guidance_scale × (cond - uncond), at the cost of requiring two forward passes per step.70% similarVerified扩散模型是一类基于马尔可夫链的生成模型，核心思想是通过前向加噪和反向去噪来捕捉数据分布69% similarVerified扩散模型的核心原理分为前向扩散过程（逐步添加高斯噪声）和反向去噪过程（从噪声中还原图像）两个阶段66% similarUnverified从30步CFG 4到12步CFG 1的加速本质上是模型蒸馏技术的应用成果，与Consistency Model、SDXL-Turbo、LCM共享相似底层思路64% similar
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