Unverified50% confidenceFactExact time
扩散模型每次从随机噪声开始去噪，相同文本提示下不同随机种子会导致面部特征、体型、服装等漂移，是角色一致性困难的技术根源
1
Sources
50%
Confidence
Long-term
Relevance
8/23/2026
First Seen
Sources
Related Entities
Related Claims
VerifiedThe results of AI image expansion differ each time, and this randomness stems from the diffusion model starting from different random noise each time79% similarUnverifiedSeed controls randomness at the noise level, and switching the seed with an unchanged prompt only produces minor differences in composition and detail texture, whereas Wildcards introduce an independent random dimension at the semantic level.74% similarUnverified主体漂移本质上是模型在时序一致性建模上的不足，源于扩散模型每帧去噪引入随机性叠加时序注意力对长程依赖捕获能力有限74% similarUnverified主流扩散模型在像素空间进行迭代去噪，文字的精确笔画结构对该过程极为敏感，细微噪声扰动会导致字形崩坏73% similarUnverifiedThe iterative denoising process of diffusion models is sensitive to numerical errors; small errors at each step accumulate and affect the final image, and the more sampling steps there are, the greater the impact of quantization errors.71% similar
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