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 # DDT: Decoupled Diffusion Transformer
-arxiv link: [https://arxiv.org/abs/2504.05741](https://arxiv.org/abs/2504.05741)
+[![arXiv](https://img.shields.io/badge/arXiv-2504.05741-b31b1b.svg)](https://arxiv.org/abs/2504.05741)
+[![Paper page](https://huggingface.co/datasets/huggingface/badges/resolve/main/paper-page-sm.svg)](https://huggingface.co/papers/2504.05741)
 
-ImagNet256 leaderboard: [https://paperswithcode.com/sota/image-generation-on-imagenet-256x256](https://paperswithcode.com/sota/image-generation-on-imagenet-256x256)
+[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/ddt-decoupled-diffusion-transformer/image-generation-on-imagenet-256x256)](https://paperswithcode.com/sota/image-generation-on-imagenet-256x256?p=ddt-decoupled-diffusion-transformer)
 
-ImagNet512 leaderboard: [https://paperswithcode.com/sota/image-generation-on-imagenet-512x512](https://paperswithcode.com/sota/image-generation-on-imagenet-512x512)
+[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/ddt-decoupled-diffusion-transformer/image-generation-on-imagenet-512x512)](https://paperswithcode.com/sota/image-generation-on-imagenet-512x512?p=ddt-decoupled-diffusion-transformer)
 ## Introduction
 We decouple diffusion transformer into encoder-decoder design, and surpresingly that a **more substantial encoder yields performance improvements as model size increases**.
 ![](./figs/main.png)