MarkupLM: Pre-training of Text and Markup Language for Visually Rich Document Understanding
Junlong Li, Yiheng Xu, Lei Cui, Furu Wei · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · 2022
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/XMLbased 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.