PRIM: Towards Practical In-Image Multilingual Machine Translation (EMNLP 2025 Main)

📄Paper arXiv | 💻Code GitHub | 🤗Training set HuggingFace | 🤗Model HuggingFace

Introduction

This repository provides the PRIM benchmark, which is introduced in our paper PRIM: Towards Practical In-Image Multilingual Machine Translation.

PRIM (Practical In-Image Multilingual Machine Translation) is the first publicly available benchmark captured from real-word images for In-Image machine Translation.

The source images are collected from [1] and [2]. We sincerely thank the authors of these datasets for making their data available.

Citation

If you find our work helpful, we would greatly appreciate it if you could cite our paper:

@misc{tian2025primpracticalinimagemultilingual,
      title={PRIM: Towards Practical In-Image Multilingual Machine Translation}, 
      author={Yanzhi Tian and Zeming Liu and Zhengyang Liu and Chong Feng and Xin Li and Heyan Huang and Yuhang Guo},
      year={2025},
      eprint={2509.05146},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2509.05146}, 
}

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[1] Modal Contrastive Learning Based End-to-End Text Image Machine Translation

[2] MIT-10M: A Large Scale Parallel Corpus of Multilingual Image Translation