README.md

---
license: mit
language:
- en
tags:
- embedding
- multimodal
- multilingual
pretty_name: XTD
size_categories:
- 1K<n<10K
configs:
- config_name: it
  data_files:
  - split: test
    path: it/it.parquet
- config_name: es
  data_files:
  - split: test
    path: es/es.parquet
- config_name: ru
  data_files:
  - split: test
    path: ru/ru.parquet
- config_name: zh
  data_files:
  - split: test
    path: zh/zh.parquet
- config_name: pl
  data_files:
  - split: test
    path: pl/pl.parquet
- config_name: tr
  data_files:
  - split: test
    path: tr/tr.parquet
- config_name: ko
  data_files:
  - split: test
    path: ko/ko.parquet
---

# XTD Multimodal Multilingual Data


This dataset contains datasets used for evaluating the multilingual capability of a multimodal embedding model, including seven languages:
- **it**
- **es**
- **ru**
- **zh**
- **pl**
- **tr**
- **ko**


## Image Preparation

First, you should prepare the images used for evaluation:

### Image Downloads

- **Download Links**: Download image resources for each dataset via the following links:
  - [**MMEB**](https://huggingface.co/datasets/TIGER-Lab/MMEB-train)
  - [**InfoSeek**](https://huggingface.co/datasets/TIGER-Lab/M-BEIR)
  - [**ArxivQA**](https://huggingface.co/datasets/MMInstruction/ArxivQA)
  - [**TAT-DQA**](https://huggingface.co/datasets/vidore/tatdqa_train/tree/main)


### Image Organization

```
  images/
  ├── XTD10_dataset/
       └── ... .png 
```

You can refer to the image paths in each subset to view the image organization.

You can also customize your image paths by altering the image_path fields.


## Citation

If you use this dataset in your research, feel free to cite the original paper of XTD and mmE5 paper.