README.md

---
license: mit
language:
- zh
- en
- fr
- de
size_categories:
- 100K<n<1M
---
# Notice for Download Application
If you would like to participate in the DIMT2025@ICDAR challenge, please download the [End User License Agreement](https://drive.google.com/file/d/1b7Z5P2h0E8AZdzUyXrfmfNkBssO6s_eL/view),
fill it out and send it to [[email protected]](mailto:[email protected]) to access the data.

<big><u>***(Please make sure to use the email address of your huggingface account to send the End User License Agreement.)***</u></big>

We will review your application and get in touch as soon as possible. 

For more information, please refer to our [official challenge website](https://cip-documentai.github.io/).

</br>
</br>
</br>


# Document Image Machine Translation with Dynamic Multi-pre-trained Models Assembling

This is the official repository for **DoTA** dataset (**Do**cument image machine **T**ranslation dataset of **A**rXiv articles in markdown format) introduced by the following paper: [***Document Image Machine Translation with Dynamic Multi-pre-trained Models Assembling (NAACL 2024 Main)***](https://aclanthology.org/2024.naacl-long.392)

In addition to the 126K samples mentioned in the paper, we provide all 139K samples that have not been filtered.
Each sample contains original English image, transcripted English mmd file and translated Chinese/French/German mmd file.
Samples used in the paper are listed in a json file.

Text files can be decompressed as follows:
```bash
tar -xzvf zh_mmd.tar.gz -C ./
```
Image files can be decompressed as follows:
```bash
cat imgs.tar.gz.* | tar -xzvf - -C ./
```

If you want to use our dataset, please cite as follows:
```BibTex
@inproceedings{liang-etal-2024-document,
    title = "Document Image Machine Translation with Dynamic Multi-pre-trained Models Assembling",
    author = "Liang, Yupu  and
      Zhang, Yaping  and
      Ma, Cong  and
      Zhang, Zhiyang  and
      Zhao, Yang  and
      Xiang, Lu  and
      Zong, Chengqing  and
      Zhou, Yu",
    editor = "Duh, Kevin  and
      Gomez, Helena  and
      Bethard, Steven",
    booktitle = "Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)",
    month = jun,
    year = "2024",
    address = "Mexico City, Mexico",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2024.naacl-long.392",
    pages = "7077--7088",
}
```