MarkupLM: Pre-training of Text and Markup Language for Visually-rich Document Understanding

• URL: http://arxiv.org/abs/2110.08518v1
• Date: Sat, 16 Oct 2021 09:17:28 GMT
• Title: MarkupLM: Pre-training of Text and Markup Language for Visually-rich Document Understanding
• Authors: Junlong Li, Yiheng Xu, Lei Cui, Furu Wei
• Abstract summary: Multimodal pre-training with text, layout, and image has made significant progress for Visually-rich Document Understanding (VrDU) We propose MarkupLM for document understanding tasks with markup languages as the backbone. Experiment results show that the pre-trained MarkupLM significantly outperforms the existing strong baseline models on several document understanding tasks.
• Score: 35.35388421383703
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Multimodal pre-training with text, layout, and image has made significant progress for Visually-rich Document Understanding (VrDU), especially the fixed-layout documents such as scanned document images. While, there are still a large number of digital documents where the layout information is not fixed and needs to be interactively and dynamically rendered for visualization, making existing layout-based pre-training approaches not easy to apply. In this paper, we propose MarkupLM for document understanding tasks with markup languages as the backbone such as HTML/XML-based documents, where text and markup information is jointly pre-trained. Experiment results show that the pre-trained MarkupLM significantly outperforms the existing strong baseline models on several document understanding tasks. The pre-trained model and code will be publicly available at https://aka.ms/markuplm.

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