先说结论。它和通用视觉自监督的关系在于：用四关键帧时序一致性 probe 静态图像生成模型的 visual world modeling 能力。 高相关；详见方法、贡献和实验边界。
Figureure 3 · | Radar view of prompt-only capability scores across all eight evaluatFigure 3 | Radar view of prompt-only capability scores across all eight evaluated models. The axes correspond to C0 and C2–C9; C1 is omitted because reference grounding is not applicable without a reference image. The faint purple envelope highlights the GPT Image 2 capability profile, while all model contours and markers are retained for comparison.这张图/表用于判断 Can Image Models Imagine Time? ImageTime 的实验收益来自哪里。重点看替换、消融或跨模型设置下趋势是否一致，而不是只看单个最高分。Figureure 7 · | Fine-grained category-level prompt-only Overall mean scoresFigure 7 | Fine-grained category-level prompt-only Overall mean scores. Rows cover all 22 ImageTime categories reconstructed from the case filename and case-id prefixes, and columns report the eight evaluated models.这张图来自论文 PDF 的结构化抽取。当前用于辅助理解 Can Image Models Imagine Time? ImageTime 的方法或实验，请结合正文精读段落一起看。
核心问题
它和通用视觉自监督的关系在于：用四关键帧时序一致性 probe 静态图像生成模型的 visual world modeling 能力。
方法拆解
用四关键帧时序一致性 probe 静态图像生成模型的 visual world modeling 能力
