Datasets:
ArXiv:
License:
license: odc-by | |
#### Mind2Web evaluation set for the paper: [Harnessing Webpage Uis For Text Rich Visual Understanding](https://arxiv.org/abs/2410.13824) | |
🌐 [Homepage](https://neulab.github.io/MultiUI/) | 🐍 [GitHub](https://github.com/neulab/multiui) | 📖 [arXiv](https://arxiv.org/abs/2410.13824) | |
## Introduction | |
We introduce **MultiUI**, a dataset containing 7.3 million samples from 1 million websites, covering diverse multi- modal tasks and UI layouts. Models trained on **MultiUI** not only excel in web UI tasks—achieving up to a 48% improvement on VisualWebBench and a 19.1% boost in action accuracy on a web agent dataset Mind2Web—but also generalize surprisingly well to non-web UI tasks and even to non-UI domains, such as document understanding, OCR, and chart interpretation. | |
<video controls autoplay src="https://cdn-uploads.huggingface.co/production/uploads/65403d8781a8731a1c09a584/vk7yT4Y7ydBOHM6BojmlI.mp4"></video> | |
## Contact | |
* Junpeng Liu: [email protected] | |
* Xiang Yue: [email protected] | |
## Citation | |
If you find this work helpful, please cite out paper: | |
```` | |
@misc{liu2024harnessingwebpageuistextrich, | |
title={Harnessing Webpage UIs for Text-Rich Visual Understanding}, | |
author={Junpeng Liu and Tianyue Ou and Yifan Song and Yuxiao Qu and Wai Lam and Chenyan Xiong and Wenhu Chen and Graham Neubig and Xiang Yue}, | |
year={2024}, | |
eprint={2410.13824}, | |
archivePrefix={arXiv}, | |
primaryClass={cs.CV}, | |
url={https://arxiv.org/abs/2410.13824}, | |
} | |
```` |