README.md

---
license: mit
language:
- en
tags:
- embedding
- multimodal
pretty_name: mmE5 labeled data
size_categories:
- 1M<n<10M
configs:
- config_name: TAT-DQA
  data_files:
    - split: train
      path: "TAT-DQA/TAT-DQA.parquet"
- config_name: ArxivQA
  data_files:
    - split: train
      path: "ArxivQA/ArxivQA.parquet"
- config_name: InfoSeek_it2t
  data_files:
    - split: train
      path: "InfoSeek_it2t/InfoSeek_it2t.parquet"
- config_name: InfoSeek_it2it
  data_files:
    - split: train
      path: "InfoSeek_it2it/InfoSeek_it2it.parquet"
- config_name: ImageNet_1K
  data_files:
    - split: train
      path: "ImageNet_1K/ImageNet_1K.parquet"
- config_name: N24News
  data_files:
    - split: train
      path: "N24News/N24News.parquet"
- config_name: HatefulMemes
  data_files:
    - split: train
      path: "HatefulMemes/HatefulMemes.parquet"
- config_name: SUN397
  data_files:
    - split: train
      path: "SUN397/SUN397.parquet"
- config_name: VOC2007
  data_files:
    - split: train
      path: "VOC2007/VOC2007.parquet"
- config_name: InfographicsVQA
  data_files:
    - split: train
      path: "InfographicsVQA/InfographicsVQA.parquet"
- config_name: ChartQA
  data_files:
    - split: train
      path: "ChartQA/ChartQA.parquet"
- config_name: A-OKVQA
  data_files:
    - split: train
      path: "A-OKVQA/A-OKVQA.parquet"
- config_name: DocVQA
  data_files:
    - split: train
      path: "DocVQA/DocVQA.parquet"
- config_name: OK-VQA
  data_files:
    - split: train
      path: "OK-VQA/OK-VQA.parquet"
- config_name: Visual7W
  data_files:
    - split: train
      path: "Visual7W/Visual7W.parquet"
- config_name: VisDial
  data_files:
    - split: train
      path: "VisDial/VisDial.parquet"
- config_name: CIRR
  data_files:
    - split: train
      path: "CIRR/CIRR.parquet"
- config_name: NIGHTS
  data_files:
    - split: train
      path: "NIGHTS/NIGHTS.parquet"
- config_name: WebQA
  data_files:
    - split: train
      path: "WebQA/WebQA.parquet"
- config_name: VisualNews_i2t
  data_files:
    - split: train
      path: "VisualNews_i2t/VisualNews_i2t.parquet"
- config_name: VisualNews_t2i
  data_files:
    - split: train
      path: "VisualNews_t2i/VisualNews_t2i.parquet"
- config_name: MSCOCO_i2t
  data_files:
    - split: train
      path: "MSCOCO_i2t/MSCOCO_i2t.parquet"
- config_name: MSCOCO_t2i
  data_files:
    - split: train
      path: "MSCOCO_t2i/MSCOCO_t2i.parquet"
- config_name: MSCOCO
  data_files:
    - split: train
      path: "MSCOCO/MSCOCO.parquet"
---
# mmE5 Labeled Data




This dataset contains datasets used for the supervised finetuning of mmE5 ([mmE5: Improving Multimodal Multilingual Embeddings via High-quality Synthetic Data](https://arxiv.org/abs/2502.08468)):
- **MMEB** (with hard negative)
- **InfoSeek** (from M-BEIR)
- **TAT-DQA**
- **ArxivQA**

[Github](https://github.com/haon-chen/mmE5)

## Image Preparation

First, you should prepare the images used for training:

### Image Downloads

- **Download All Images Used in mmE5**:

You can use the script provided in our [source code](https://github.com/haon-chen/mmE5) to download all images used in mmE5.
```bash
git clone https://github.com/haon-chen/mmE5.git
cd mmE5
bash scripts/prepare_images.sh
```

### Image Organization

```
  images/
  ├── mbeir_images/
  │     └── oven_images/
  │           └── ... .jpg (InfoSeek)
  ├── ArxivQA/
  │     └── images/
  │           └── ... .jpg (ArxivQA)
  └── TAT-DQA/
  │     └── ... .png (TAT-DQA)
  └── A-OKVQA/
        └── Train/
  │           └── ... .jpg (A-OKVQA)
  │
  ... (MMEB Training images)
```

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, please cite the associated paper.
```
@article{chen2025mmE5,
  title={mmE5: Improving Multimodal Multilingual Embeddings via High-quality Synthetic Data},
  author={Chen, Haonan and Wang, Liang and Yang, Nan and Zhu, Yutao and Zhao, Ziliang and Wei, Furu and Dou, Zhicheng},
  journal={arXiv preprint arXiv:2502.08468},
  year={2025}
}
```