Dimensions overall score 7.0

• ZEUS achieves up to 3.2x end-to-end speedup while maintaining perceptual quality in image and video generation.result 90%
• ZEUS uses a second-order predictor to reduce denoiser evaluations during sampling.method 85%
• ZEUS adds essentially zero overhead, no feature caches, and no architectural modifications.technical 90%
• ZEUS is compatible with different backbones, prediction objectives, and solver choices.technical 85%
• Current training-free acceleration methods are more complex than necessary for diffusion model acceleration.limitation 80%
• Higher-order predictors amplify error under aggressive speedups in current acceleration methods.limitation 80%
• ZEUS stabilizes aggressive consecutive skipping with an interleaved scheme that avoids back-to-back extrapolations.method 85%
• Beyond 2x acceleration, step skipping creates structural scarcity with at most one fresh evaluation per local window.technical 75%

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