|
--- |
|
license: apache-2.0 |
|
configs: |
|
- config_name: default |
|
data_files: |
|
- split: train |
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path: |
|
- train/EN.jsonl |
|
- train/ZH.jsonl |
|
- train/PT.jsonl |
|
- train/JA.jsonl |
|
- train/FR.jsonl |
|
- train/ES.jsonl |
|
- train/IT.jsonl |
|
- train/DE.jsonl |
|
- split: test |
|
path: |
|
- test/EN.jsonl |
|
- test/ZH.jsonl |
|
- test/PT.jsonl |
|
- test/JA.jsonl |
|
- test/FR.jsonl |
|
- test/ES.jsonl |
|
- test/IT.jsonl |
|
- test/DE.jsonl |
|
language: |
|
- en |
|
- zh |
|
- pt |
|
- ja |
|
- fr |
|
- es |
|
- it |
|
- de |
|
- ru |
|
- ar |
|
- ko |
|
- tr |
|
- th |
|
- hi |
|
task_categories: |
|
- translation |
|
- image-to-text |
|
size_categories: |
|
- 10M<n<100M |
|
--- |
|
|
|
## MIT-10M |
|
|
|
**Paper:** https://aclanthology.org/2025.coling-main.346/ |
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|
|
**Introduction:** |
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|
|
Image Translation (IT) holds immense potential across diverse domains, enabling the translation of textual content within images into various languages. |
|
However, existing datasets often suffer from limitations in scale, diversity, and quality, hindering the development and evaluation of IT models. |
|
To address this issue, we introduce MIT-10M, a large-scale parallel corpus of multilingual image translation with over 10M image-text pairs derived from real-world data, which has undergone extensive data cleaning and multilingual translation validation. |
|
It contains 0.8M images in three sizes, 28 categories, tasks with three levels of difficulty and 14 languages image-text pairs, which is a considerable improvement on existing datasets. |
|
|
|
|
|
|
|
|
|
### Citation Information |
|
You can cite our paper https://aclanthology.org/2025.coling-main.346/ |
|
``` |
|
@inproceedings{li-etal-2025-mit, |
|
title = "{MIT}-10{M}: A Large Scale Parallel Corpus of Multilingual Image Translation", |
|
author = "Li, Bo and Zhu, Shaolin and Wen, Lijie", |
|
booktitle = "Proceedings of the 31st International Conference on Computational Linguistics", |
|
month = jan, |
|
year = "2025", |
|
address = "Abu Dhabi, UAE", |
|
publisher = "Association for Computational Linguistics", |
|
url = "https://aclanthology.org/2025.coling-main.346/", |
|
pages = "5154--5167" |
|
} |
|
|
|
``` |
|
|
