Fetching the paper…
Reading the bibliography…
Tables contain factual and quantitative data accompanied by various structures and contents that pose challenges for machine comprehension.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 1901
Earlier work this paper cites.
The t-recs table recognition and analysis system
Thomas Kieninger and Andreas Dengel · 1999
Earlier work this paper cites.
Automatic table detection in document images
Basilios Gatos, Dimitrios Danatsas, Ioannis Pratikakis, and Stavros J Perantonis · 2005
Earlier work this paper cites.
End-to-end scene text recognition
Kai Wang, Boris Babenko, and Serge Belongie · 2011
Earlier work this paper cites.
Table detection in document images using header and trailer patterns
Gaurav Harit and Anukriti Bansal · 2012
Earlier work this paper cites.
Icdar 2013 table competition
Max Gobel, Tamir Hassan, Ermelinda Oro, and Giorgio Orsi · 2013
Earlier work this paper cites.
Compositional semantic parsing on semi-structured tables
Panupong Pasupat and Percy Liang · 2015
Earlier work this paper cites.
Fast R-CNN
Ross Girshick · 2015
Earlier work this paper cites.
Faster R-CNN: Towards real-time object detection with region proposal networks
Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun · 2015
Earlier work this paper cites.
Deepdesrt: Deep learning for detection and structure recognition of tables in document images
Sebastian Schreiber, Stefan Agne, Ivo Wolf, Andreas Dengel, and Sheraz Ahmed · 2017
Earlier work this paper cites.
Table detection using deep learning
Azka Gilani, Shah Rukh Qasim, Imran Malik, and Faisal Shafait · 2017
Earlier work this paper cites.
Mask R-CNN
Kaiming He, Georgia Gkioxari, Piotr Dollár, and Ross Girshick · 2017
Earlier work this paper cites.
DeCNT: Deep deformable cnn for table detection
Shoaib Ahmed Siddiqui, Muhammad Imran Malik, Stefan Agne, Andreas Dengel, and Sheraz Ahmed · 2018
Earlier work this paper cites.
Improving language understanding by generative pre-training
Alec Radford, Karthik Narasimhan, Tim Salimans, Ilya Sutskever, et al · 2018
Earlier work this paper cites.
Ensemble of deep object detectors for page object detection
Nguyen D Vo, Khanh Nguyen, Tam V Nguyen, and Khang Nguyen · 2018
Earlier work this paper cites.
Fots: Fast oriented text spotting with a unified network
Xuebo Liu, Ding Liang, Shi Yan, Dagui Chen, Yu Qiao, and Junjie Yan · 2018
Earlier work this paper cites.
Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2018
Earlier work this paper cites.
Icdar 2019 competition on table detection and recognition (ctdar)
Liangcai Gao, Yilun Huang, Herve Dejean, Jean-Luc Meunier, Qinqin Yan, Yu Fang, Florian Kleber, and Eva Lang · 2019
Earlier work this paper cites.
A yolo-based table detection method
Yilun Huang, Qinqin Yan, Yibo Li, Yifan Chen, Xiong Wang, Liangcai Gao, and Zhi Tang · 2019
Earlier work this paper cites.
Faster r-cnn based table detection combining corner locating
Ningning Sun, Yuanping Zhu, and Xiaoming Hu · 2019
Earlier work this paper cites.
Table detection in invoice documents by graph neural networks
Pau Riba, Anjan Dutta, Lutz Goldmann, Alicia Fornés, Oriol Ramos, and Josep Lladós · 2019
Earlier work this paper cites.
Table understanding in structured documents
Martin Holeček, Antonín Hoskovec, Petr Baudiš, and Pavel Klinger · 2019
Earlier work this paper cites.
TableNet: Deep learning model for end-to-end table detection and tabular data extraction from scanned document images
Shubham Singh Paliwal, D Vishwanath, Rohit Rahul, Monika Sharma, and Lovekesh Vig · 2019
Earlier work this paper cites.
Complicated table structure recognition
Zewen Chi, Heyan Huang, Heng-Da Xu, Houjin Yu, Wanxuan Yin, and Xian-Ling Mao · 2019
Earlier work this paper cites.
A comprehensive survey of deep learning for image captioning
MD Zakir Hossain, Ferdous Sohel, Mohd Fairuz Shiratuddin, and Hamid Laga · 2019
Earlier work this paper cites.
TabFact: A large-scale dataset for table-based fact verification
Wenhu Chen, Hongmin Wang, Jianshu Chen, Yunkai Zhang, Hong Wang, Shiyang Li, Xiyou Zhou, and William Yang Wang · 2019
Earlier work this paper cites.
Super-convergence: Very fast training of neural networks using large learning rates
Leslie N Smith and Nicholay Topin · 2019
Earlier work this paper cites.
PyTorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, et al · 2019
Cited alongside, same era.
An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, et al · 2020
Cited alongside, same era.
BART: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension
Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Veselin Stoyanov, and Luke Zettlemoyer · 2020
Cited alongside, same era.
Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J Liu · 2020
Cited alongside, same era.
Docbank: A benchmark dataset for document layout analysis
Minghao Li, Yiheng Xu, Lei Cui, Shaohan Huang, Furu Wei, Zhoujun Li, and Ming Zhou · 2020
Kosmos-2: Grounding multimodal large language models to the world
Zhiliang Peng, Wenhui Wang, Li Dong, Yaru Hao, Shaohan Huang, Shuming Ma, and Furu Wei · 2023
Later among the works it cites.
MiniGPT-4: Enhancing vision-language understanding with advanced large language models
Deyao Zhu, Jun Chen, Xiaoqian Shen, Xiang Li, and Mohamed Elhoseiny · 2023
Later among the works it cites.
Shikra: Unleashing multimodal llm’s referential dialogue magic
Keqin Chen, Zhao Zhang, Weili Zeng, Richong Zhang, Feng Zhu, and Rui Zhao · 2023
Later among the works it cites.
The dawn of lmms: Preliminary explorations with gpt-4v (ision)
Zhengyuan Yang, Linjie Li, Kevin Lin, Jianfeng Wang, Chung-Ching Lin, Zicheng Liu, and Lijuan Wang · 2023
Later among the works it cites.
Gpt-4 technical report, 2023
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
End-to-end object detection with transformers
Nicolas Carion, Francisco Massa, Gabriel Synnaeve, Nicolas Usunier, Alexander Kirillov, and Sergey Zagoruyko · 2020
Cited alongside, same era.
Image-based table recognition: data, model, and evaluation
Xu Zhong, Elaheh ShafieiBavani, and Antonio Jimeno Yepes · 2020
Cited alongside, same era.
Mikhail S Burtsev, Yuri Kuratov, Anton Peganov, and Grigory V Sapunov · 2020
Cited alongside, same era.
Real-time scene text detection with differentiable binarization
Minghui Liao, Zhaoyi Wan, Cong Yao, Kai Chen, and Xiang Bai · 2020
Cited alongside, same era.
Global table extractor (gte): A framework for joint table identification and cell structure recognition using visual context
Xinyi Zheng, Douglas Burdick, Lucian Popa, Xu Zhong, and Nancy Xin Ru Wang · 2021
Cited alongside, same era.
Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
Cited alongside, same era.
Cdec-net: Composite deformable cascade network for table detection in document images
Madhav Agarwal, Ajoy Mondal, and CV Jawahar · 2021
Cited alongside, same era.
OpenAI · 2023
Later among the works it cites.
Rohan Anil, Andrew M Dai, Orhan Firat, Melvin Johnson, Dmitry Lepikhin, Alexandre Passos, Siamak Shakeri, Emanuel Taropa, Paige Bailey, Zhifeng Chen, et al · 2023
Later among the works it cites.
Llama-adapter v2: Parameter-efficient visual instruction model
Peng Gao, Jiaming Han, Renrui Zhang, Ziyi Lin, Shijie Geng, Aojun Zhou, Wei Zhang, Pan Lu, Conghui He, Xiangyu Yue, et al · 2023
Later among the works it cites.
Introducing qwen-7b: Open foundation and human-aligned models (of the state-of-the-arts), 2023
Qwen · 2023
Later among the works it cites.
Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality
Wei-Lin Chiang, Zhuohan Li, Zi Lin, Ying Sheng, Zhanghao Wu, Hao Zhang, Lianmin Zheng, Siyuan Zhuang, Yonghao Zhuang, Joseph E Gonzalez, et al · 2023
Later among the works it cites.
Vary: Scaling up the vision vocabulary for large vision-language models
Haoran Wei, Lingyu Kong, Jinyue Chen, Liang Zhao, Zheng Ge, Jinrong Yang, Jianjian Sun, Chunrui Han, and Xiangyu Zhang · 2023
Later among the works it cites.
In-context autoencoder for context compression in a large language model
Tao Ge, Hu Jing, Lei Wang, Xun Wang, Si-Qing Chen, and Furu Wei · 2023
Later among the works it cites.
Adaptive computation with elastic input sequence
Fuzhao Xue, Valerii Likhosherstov, Anurag Arnab, Neil Houlsby, Mostafa Dehghani, and Yang You · 2023
Later among the works it cites.
Vision transformers need registers
Timothée Darcet, Maxime Oquab, Julien Mairal, and Piotr Bojanowski · 2023
Later among the works it cites.
Think before you speak: Training language models with pause tokens
Sachin Goyal, Ziwei Ji, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar, and Vaishnavh Nagarajan · 2023
Later among the works it cites.
DINOv2: Learning robust visual features without supervision
Maxime Oquab, Timothée Darcet, Théo Moutakanni, Huy V Vo, Marc Szafraniec, Vasil Khalidov, Pierre Fernandez, Daniel HAZIZA, Francisco Massa, Alaaeldin El-Nouby, et al · 2023
Later among the works it cites.
Pix2struct: Screenshot parsing as pretraining for visual language understanding
Kenton Lee, Mandar Joshi, Iulia Raluca Turc, Hexiang Hu, Fangyu Liu, Julian Martin Eisenschlos, Urvashi Khandelwal, Peter Shaw, Ming-Wei Chang, and Kristina Toutanova · 2023
Later among the works it cites.
UReader: Universal ocr-free visually-situated language understanding with multimodal large language model
Jiabo Ye, Anwen Hu, Haiyang Xu, Qinghao Ye, Ming Yan, Guohai Xu, Chenliang Li, Junfeng Tian, Qi Qian, Ji Zhang, et al · 2023
Later among the works it cites.
GriTS: Grid table similarity metric for table structure recognition
Brandon Smock, Rohith Pesala, and Robin Abraham · 2023
Later among the works it cites.
On the hidden mystery of ocr in large multimodal models
Yuliang Liu, Zhang Li, Hongliang Li, Wenwen Yu, Mingxin Huang, Dezhi Peng, Mingyu Liu, Mingrui Chen, Chunyuan Li, Lianwen Jin, et al · 2023
Later among the works it cites.
Cogagent: A visual language model for gui agents
Wenyi Hong, Weihan Wang, Qingsong Lv, Jiazheng Xu, Wenmeng Yu, Junhui Ji, Yan Wang, Zihan Wang, Yuxiao Dong, Ming Ding, et al · 2023
Later among the works it cites.
mPLUG-DocOwl 1.5: Unified structure learning for ocr-free document understanding
Anwen Hu, Haiyang Xu, Jiabo Ye, Ming Yan, Liang Zhang, Bo Zhang, Chen Li, Ji Zhang, Qin Jin, Fei Huang, et al · 2024
Closest in time.
OmniParser: A unified framework for text spotting, key information extraction and table recognition
Jianqiang Wan, Sibo Song, Wenwen Yu, Yuliang Liu, Wenqing Cheng, Fei Huang, Xiang Bai, Cong Yao, and Zhibo Yang · 2024
Closest in time.
ShengYun Peng, Seongmin Lee, Xiaojing Wang, Rajarajeswari Balasubramaniyan, and Duen Horng Chau · 2024
Closest in time.
LayoutLLM: Large language model instruction tuning for visually rich document understanding
Masato Fujitake · 2024
Closest in time.
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
Machel Reid, Nikolay Savinov, Denis Teplyashin, Dmitry Lepikhin, Timothy Lillicrap, Jean-baptiste Alayrac, Radu Soricut, Angeliki Lazaridou, Orhan Firat, Julian Schrittwieser, et al · 2024
Closest in time.
Xiaoyi Dong, Pan Zhang, Yuhang Zang, Yuhang Cao, Bin Wang, Linke Ouyang, Xilin Wei, Songyang Zhang, Haodong Duan, Maosong Cao, et al · 2024
Closest in time.