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A stochastic few-step generator whose FID does not degrade as the sampling budget grows from 4 to 50 NFE, and the same recipe transfers to text-to-image generation.
The Logit Refiner is introduced, a lightweight autoregressive module that restores intra-scale dependencies by sequentially sampling tokens conditioned on frozen backbone features and generalizes to text-to-image generation, confirming that the mean-field bottleneck persists across VAR variants and is effectively allev...
A novel notion of concept-wise mutual information is introduced and large, concept-dependent differences between individual layers are found, demonstrating that the generation of specific structures is localized in distinct parts of the network.
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