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Dense prediction can achieve state-of-the-art performance by leveraging generative pretraining without the overhead of RGB content generation.
Removing inter-token interactions in diffusion models surprisingly boosts performance, revealing that data augmentation is the real driver behind improvements from SRA to Self-Flow.
