Unverified50% confidenceFactExact time
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
1
Sources
50%
Confidence
Long-term
Relevance
7/8/2026
First Seen
Sources
Ideogram 4本地部署实测：8G显存跑出大片质感
bilibili秋叶comfyui教学视频7/3/2026
Related Claims
Unverified扩散模型的迭代去噪过程对数值误差敏感，每步的微小误差会累积并影响最终图像，采样步数越多量化误差影响越大73% similarVerified文档切分策略中切分过细会丢失上下文，切分过粗会引入噪声71% similarUnverified如果设定的时长超过了实际提供的内容量，模型会用无意义的杂音去填补空白71% similarUnverified上下文中存在相互冲突或交替出现的格式约束，会显著提升模型的幻觉率和格式错误率70% 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68% similar
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