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Structured document understanding has attracted considerable attention and made significant progress recently, owing to its crucial role in intelligent document processing.
RoBERTa: A robustly optimized BERT pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019b · 1907
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Modular multimodal architecture for document classification
Tyler Dauphinee, Nikunj Patel, and Mohammad Rashidi. 2019 · 1912
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Building a test collection for complex document information processing
David Lewis, Gady Agam, Shlomo Argamon, Ophir Frieder, David Grossman, and Jefferson Heard. 2006 · 2006
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Evaluation of deep convolutional nets for document image classification and retrieval
Adam W Harley et al. 2015 · 2015
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba. 2015 · 2015
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Jimmy Lei Ba, Jamie Ryan Kiros, and Geoffrey E Hinton. 2016 · 2016
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Neural architectures for named entity recognition
Guillaume Lample, Miguel Ballesteros, Sandeep Subramanian, Kazuya Kawakami, and Chris Dyer. 2016 · 2016
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Cutting the error by half: Investigation of very deep CNN and advanced training strategies for document image classification
Muhammad Zeshan Afzal, Andreas Kölsch, Sheraz Ahmed, and Marcus Liwicki. 2017 · 2017
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Fast CNN-based document layout analysis
Dario Augusto Borges Oliveira et al. 2017 · 2017
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Feature pyramid networks for object detection
Tsung-Yi Lin, Piotr Dollár, Ross Girshick, Kaiming He, Bharath Hariharan, and Serge Belongie. 2017 · 2017
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Inception-v4, Inception-ResNet and the impact of residual connections on learning
Christian Szegedy, Sergey Ioffe, Vincent Vanhoucke, and Alexander A Alemi. 2017 · 2017
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Aggregated residual transformations for deep neural networks
Saining Xie, Ross Girshick, Piotr Dollár, Zhuowen Tu, and Kaiming He. 2017 · 2017
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Learning to extract semantic structure from documents using multimodal fully convolutional neural networks
Xiao Yang, Ersin Yumer, Paul Asente, Mike Kraley, Daniel Kifer, and C Lee Giles. 2017 · 2017
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Document image classification with intra-domain transfer learning and stacked generalization of deep convolutional neural networks
Arindam Das, Saikat Roy, Ujjwal Bhattacharya, and Swapan K Parui. 2018 · 2018
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Chargrid: Towards understanding 2D documents
Anoop R Katti, Christian Reisswig, Cordula Guder, Sebastian Brarda, Steffen Bickel, Johannes Höhne, and Jean Baptiste Faddoul. 2018 · 2018
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter. 2018 · 2018
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Extracting scientific figures with distantly supervised neural networks
Noah Siegel, Nicholas Lourie, Russell Power, and Waleed Ammar. 2018 · 2018
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BERTgrid: Contextualized embedding for 2D document representation and understanding
Timo I Denk and Christian Reisswig. 2019 · 2019
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UniLMv2: Pseudo-masked language models for unified language model pre-training
Hangbo Bao, Li Dong, Furu Wei, Wenhui Wang, Nan Yang, Xiaodong Liu, Yu Wang, Jianfeng Gao, Songhao Piao, Ming Zhou, et al. 2020 · 2020
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Unsupervised cross-lingual representation learning at scale
Alexis Conneau, Kartikay Khandelwal, Naman Goyal, Vishrav Chaudhary, Guillaume Wenzek, Francisco Guzmán, Édouard Grave, Myle Ott, Luke Zettlemoyer, and Veselin Stoyanov. 2020 · 2020
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Revisiting pre-trained models for Chinese natural language processing
Yiming Cui, Wanxiang Che, Ting Liu, Bing Qin, Shijin Wang, and Guoping Hu. 2020 · 2020
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BROS: A pre-trained language model for understanding texts in document
Teakgyu Hong, DongHyun Kim, Mingi Ji, Wonseok Hwang, Daehyun Nam, and Sungrae Park. 2020 · 2020
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LayoutLM: Pre-training of text and layout for document image understanding
Yiheng Xu, Minghao Li, Lei Cui, Shaohan Huang, Furu Wei, and Ming Zhou. 2020 · 2020
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Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Cited alongside, same era.
FUNSD: A dataset for form understanding in noisy scanned documents
Guillaume Jaume et al. 2019 · 2019
Cited alongside, same era.
ViLBERT: Pretraining task-agnostic visiolinguistic representations for vision-and-language tasks
Jiasen Lu, Dhruv Batra, Devi Parikh, and Stefan Lee. 2019 · 2019
Cited alongside, same era.
CORD: A consolidated receipt dataset for post-OCR parsing
Seunghyun Park, Seung Shin, Bado Lee, Junyeop Lee, Jaeheung Surh, Minjoon Seo, and Hwalsuk Lee. 2019 · 2019
Cited alongside, same era.
GraphIE: A graph-based framework for information extraction
Yujie Qian, Enrico Santus, Zhijing Jin, Jiang Guo, and Regina Barzilay. 2019 · 2019
Cited alongside, same era.
Deterministic routing between layout abstractions for multi-scale classification of visually rich documents
Ritesh Sarkhel and Arnab Nandi. 2019 · 2019
Cited alongside, same era.
TRIE: End-to-end text reading and information extraction for document understanding
Peng Zhang, Yunlu Xu, Zhanzhan Cheng, Shiliang Pu, Jing Lu, Liang Qiao, Yi Niu, and Fei Wu. 2020 · 2019
Cited alongside, same era.
DocFormer: End-to-end Transformer for document understanding
Srikar Appalaraju, Bhavan Jasani, Bhargava Urala Kota, Yusheng Xie, and R Manmatha. 2021 · 2021
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InfoXLM: An information-theoretic framework for cross-lingual language model pre-training
Zewen Chi, Li Dong, Furu Wei, Nan Yang, Saksham Singhal, Wenhui Wang, Xia Song, Xian-Ling Mao, He-Yan Huang, and Ming Zhou. 2021 · 2021
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LAMBERT: Layout-aware (language) modeling using BERT for information extraction
Łukasz Garncarek, Rafał Powalski, Tomasz Stanisławek, Bartosz Topolski, Piotr Halama, and Filip Graliński. 2021 · 2021
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ViBERTgrid: A jointly trained multi-modal 2D document representation for key information extraction from documents
Weihong Lin, Qifang Gao, Lei Sun, Zhuoyao Zhong, Kai Hu, Qin Ren, and Qiang Huo. 2021 · 2021
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Going full-TILT boogie on document understanding with text-image-layout Transformer
Rafał Powalski, Łukasz Borchmann, Dawid Jurkiewicz, Tomasz Dwojak, Michał Pietruszka, and Gabriela Pałka. 2021 · 2021
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MatchVIE: Exploiting match relevancy between entities for visual information extraction
Guozhi Tang, Lele Xie, Lianwen Jin, Jiapeng Wang, Jingdong Chen, Zhen Xu, Qianying Wang, Yaqiang Wu, and Hui Li. 2021 · 2021
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PICK: Processing key information extraction from documents using improved graph learning-convolutional networks
Wenwen Yu, Ning Lu, Xianbiao Qi, Ping Gong, and Rong Xiao. 2021 · 2021
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