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{}
---
<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
MonoGPT is an autoregressive language model pre-trained on the dual modality of both pixels and texts without relying on the pixel-text paired data. By processing documents as visual data (pixels), the model learns to predict both the next token and the next image patch in a sequence, enabling it to handle visually complex tasks in different modalities.
## Citation
```
@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},
}
``` |