rogerdehe/xfund

XFUND是一个人类标注的多语言表单理解基准数据集，包含7种语言（中文、日语、西班牙语、法语、意大利语、德语、葡萄牙语）的表单理解样本。该数据集旨在通过多模态预训练模型LayoutXLM，跨越语言障碍，提升视觉丰富文档理解的能力。实验结果表明，LayoutXLM模型在XFUND数据集上显著优于现有的跨语言预训练模型。

原始信息汇总

XFUND数据集概述

数据集基本信息

• 名称: XFUND
• 语言: 多语言，包括德语、西班牙语、法语、意大利语、日语
• 许可证: 其他
• 多语言性: 多语言

数据集详细描述

• 任务类别: 文本分类
• 标签: layoutlmv3, xfund, funsd
• 创建者:
  • 语言创建者: 已找到
  • 注释创建者: 已找到

引用信息

latex @inproceedings{xu-etal-2022-xfund, title = "{XFUND}: A Benchmark Dataset for Multilingual Visually Rich Form Understanding", author = "Xu, Yiheng and Lv, Tengchao and Cui, Lei and Wang, Guoxin and Lu, Yijuan and Florencio, Dinei and Zhang, Cha and Wei, Furu", booktitle = "Findings of the Association for Computational Linguistics: ACL 2022", month = may, year = "2022", address = "Dublin, Ireland", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/2022.findings-acl.253", doi = "10.18653/v1/2022.findings-acl.253", pages = "3214--3224", abstract = "Multimodal pre-training with text, layout, and image has achieved SOTA performance for visually rich document understanding tasks recently, which demonstrates the great potential for joint learning across different modalities. However, the existed research work has focused only on the English domain while neglecting the importance of multilingual generalization. In this paper, we introduce a human-annotated multilingual form understanding benchmark dataset named XFUND, which includes form understanding samples in 7 languages (Chinese, Japanese, Spanish, French, Italian, German, Portuguese). Meanwhile, we present LayoutXLM, a multimodal pre-trained model for multilingual document understanding, which aims to bridge the language barriers for visually rich document understanding. Experimental results show that the LayoutXLM model has significantly outperformed the existing SOTA cross-lingual pre-trained models on the XFUND dataset. The XFUND dataset and the pre-trained LayoutXLM model have been publicly available at https://aka.ms/layoutxlm.", }