intfloat/mmE5-MMEB-hardneg

mmE5 Labeled Data

This dataset contains datasets used for the supervised finetuning of mmE5 (mmE5: Improving Multimodal Multilingual Embeddings via High-quality Synthetic Data):

• MMEB (with hard negative)
• InfoSeek (from M-BEIR)
• TAT-DQA
• ArxivQA

Github

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 to download all images used in mmE5.

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}
}