Generative models· 2022
Scalable Diffusion Models with Transformers
DOI 10.1109/iccv51070.2023.00387arXiv 2212.09748OpenAlex W4390872297
On the reading lists
- #272 in the Top 500 (2026 edition)
- #16 in Generative models (2026 edition)
Why it matters
Introduced DiT, replacing convolutional denoisers with scalable transformer architectures.
Condensed from the expert lists' notes.
The record
- First released
- 2022 (from arXiv 2212.09748)
- Citations
- 7,698 citations, as counted by Papers With Code (CC BY-SA 4.0)
- Named by
- both expert lists
- Score
- 0.466 · computed rank 272 · consensus 0.49, must-read 0.5, citations percentile 0.769 (2020s · generative-models), awards 0, existing lists 0. Method
Data sources
Catalogue data from OpenAlex (CC0), Crossref (CC0 metadata; no abstracts are shown), arXiv, and Papers With Code (CC BY-SA 4.0). Each count names its source. See the method.