LayoutLMv2: Multi-modal Pre-training for Visually-rich Document Understanding-Reference-Cited by-同舟云学术

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LayoutLMv2: Multi-modal Pre-training for Visually-rich Document Understanding

Published:2021 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)
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Author:

Xu Yang,Xu Yiheng,Lv Tengchao,Cui Lei,Wei Furu,Wang Guoxin,Lu Yijuan,Florencio Dinei,Zhang Cha,Che Wanxiang,Zhang Min,Zhou Lidong

Publisher

Association for Computational Linguistics

Cited by 152 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. LORE++: Logical location regression network for table structure recognition with pre-training;Pattern Recognition;2025-01

2. Continuous document layout analysis: Human-in-the-loop AI-based data curation, database, and evaluation in the domain of public affairs;Information Fusion;2024-08

3. Deep learning approaches for information extraction from visually rich documents: datasets, challenges and methods;International Journal on Document Analysis and Recognition (IJDAR);2024-07-29

4. A task‐centric knowledge graph construction method based on multi‐modal representation learning for industrial maintenance automation;Engineering Reports;2024-07-07

5. Enhancing Document Information Analysis with Multi-Task Pre-training: A Robust Approach for Information Extraction in Visually-Rich Documents;2024 International Joint Conference on Neural Networks (IJCNN);2024-06-30

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