Update README.md

README.md

@@ -3,16 +3,25 @@
 # Doc / guide: https://huggingface.co/docs/hub/model-cards
 {}
 ---
-This is the official checkpoint for PixelGPT, as featured in the paper [Dual Modalities of Text: Visual and Textual Generative Pre-training](https://arxiv.org/abs/2404.10710). For more details on how to use it, please visit the [GitHub page](https://github.com/ernie-research/pixelgpt).
+
+ <a href="https://2024.emnlp.org/" target="_blank"> <img alt="EMNLP 2024" src="https://img.shields.io/badge/Proceedings-EMNLP2024-red" /> </a>
+
+
+This repository contains the official checkpoint for PixelGPT, as presented in the paper [Autoregressive Pre-Training on Pixels and Texts (EMNLP 2024)](https://arxiv.org/pdf/2404.10710). For detailed instructions on how to use the model, please visit our [GitHub page](https://github.com/ernie-research/pixelgpt/).
+
 ## Model Description
-[More Information Needed]
+PixelGPT is an autoregressive language model pre-trained exclusively on pixel data using a next patch prediction objective. By processing documents as visual data (pixels), the model learns to predict the next image patch in a sequence, enabling it to handle visually complex tasks without relying on tokenized text. This tokenization-free approach allows PixelGPT to process and understand text rendered as images.
+
 
 ## Citation
 ```
-@article{chai2024dual,
-  title={Dual Modalities of Text: Visual and Textual Generative Pre-training},
-  author={Chai, Yekun and Liu, Qingyi and Xiao, Jingwu and Wang, Shuohuan and Sun, Yu and Wu, Hua},
-  journal={arXiv preprint arXiv:2404.10710},
-  year={2024}
+@misc{chai2024autoregressivepretrainingpixelstexts,
+  title = {Autoregressive Pre-Training on Pixels and Texts},
+  author = {Chai, Yekun and Liu, Qingyi and Xiao, Jingwu and Wang, Shuohuan and Sun, Yu and Wu, Hua},
+  year = {2024},
+  eprint = {2404.10710},
+  archiveprefix = {arXiv},
+  primaryclass = {cs.CL},
+  url = {https://arxiv.org/abs/2404.10710},
 }
 ```