: Standard AR models generate images in a fixed "raster" order (like reading a book), which limits their ability to understand the whole image at once. RAR introduces Randomized Autoregressive modeling , which randomly permutes the order of image tokens during training.
Paper Overview: Randomized Autoregressive Visual Generation (RAR) 868_1_RP.rar
If you have downloaded this specific file and need to access its contents (which typically include code, models, or datasets), you will need specialized software: : Standard AR models generate images in a
: It achieved a Frechet Inception Distance (FID) score of 1.48 on the ImageNet-256 benchmark, outperforming many leading diffusion-based and masked transformer models. : Always scan downloaded archives with antivirus software
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: The model starts with high randomness (permuted order) and gradually returns to the standard raster order as training progresses.