Stanford's Level-of-Token Diffusion allocates fine tokens only where detail matters
GordonWetzstein · x · 2026-10-07
- Gordon Wetzstein's group introduces Level-of-Token (LoT) Diffusion: diffusion models spend equal compute on a blank wall and a face, yet you often know in advance where detail will be.
- The method encodes that prior as a multiresolution token layout—fine tokens where detail is needed, coarse tokens elsewhere—concentrating compute on what matters.
- An architecture/sampling-level efficiency improvement; the post is thread 1/9.
Related event: Stanford's Level-of-Token Diffusion Speeds Up Generation Up to 4.6x(4 posts)→
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