Know then Draw: language-supervised visual pretraining scales pixel diffusion
CSProfKGD · x · 2026-10-29
A new paper proposes pretraining with autoregression using language-supervised visual tokenization without pixel loss, then post-training a pixel diffusion model. Fitted scaling laws and experiments show this benefits visual generation scaling. The hierarchy: AR learns what to draw, diffusion learns how — mirroring LLM pretrain-for-knowledge, post-train-for-behavior, and conceptually resembling text-rewrite conditioning in frontier image models.
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