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

**Authors:** Junlong Li, Yiheng Xu, Lei Cui, Furu Wei  
**arXiv:** [2110.08518](https://arxiv.org/abs/2110.08518)  
**Date:** 2021-10-16  
**Summary page:** https://www.summarizepaper.com/fr/paper/2110.08518v1/

## 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.