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PixelDiT: Pixel Diffusion Transformers for Image Generation research paper by NVIDIA, 2025

NVIDIA · Nov 25, 2025 · Multimodal and robotics · 71 citations · 38 upvotes · unverified

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What it shows

PixelDiT is a single-stage, end-to-end diffusion model that operates directly in pixel space, overcoming the limitations of latent-space modeling by using a dual-level transformer architecture and achieving competitive performance in image and text-to-image generation.

UnverifiedHugging Face's summary; not yet checked by hand.

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About this paper
Authors
Yongsheng Yu, Wei Xiong, Weili Nie and 3 more
arXiv
2511.20645 · PDF
Venue
arXiv.org
Citations
71, 13 influential · Semantic Scholar
Upvotes
38 · Hugging Face
Lab
NVIDIA · on Companies · on Acquisitions · on Quarterly · on Paydays · on TechConf

Changes

What changed
Influential citationsfirst count: 13Sep 25, 2026
Citationsfirst count: 71Sep 25, 2026
New paperFound by the weekly scan, unverifiedSep 25, 2026

Sources: each lab's own papers and arXiv, with citation and upvote counts from Semantic Scholar and Hugging Face. One-line summaries are for orientation, not a substitute for the paper. Logos via logo.dev; trademarks belong to their owners.

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