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Existing work on tabular representation learning jointly models tables and associated text using self-supervised objective functions derived from pretrained language models such as BERT.
Roberta: A robustly optimized bert pretraining approach
Y. Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, M. Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 1907
Earlier work this paper cites.
Quantifying the carbon emissions of machine learning
Alexandre Lacoste, Alexandra Luccioni, Victor Schmidt, and Thomas Dandres. 2019 · 1910
Earlier work this paper cites.
Generic schema matching with cupid
Jayant Madhavan, Philip A. Bernstein, and Erhard Rahm. 2001 · 2001
Earlier work this paper cites.
A survey of approaches to automatic schema matching
Erhard Rahm and Philip A. Bernstein. 2001 · 2001
Earlier work this paper cites.
Corpus-based schema matching
Jayant Madhavan, Philip A. Bernstein, AnHai Doan, and Alon Halevy. 2005 · 2005
Earlier work this paper cites.
Table-processing paradigms: a research survey
D. Embley, Matthew Hurst, D. Lopresti, and G. Nagy. 2006 · 2006
Earlier work this paper cites.
Yago: A core of semantic knowledge
Fabian M. Suchanek, Gjergji Kasneci, and Gerhard Weikum. 2007 · 2007
Earlier work this paper cites.
Webtables: Exploring the power of tables on the web
Michael J. Cafarella, Alon Halevy, Daisy Zhe Wang, Eugene Wu, and Yang Zhang. 2008 · 2008
Earlier work this paper cites.
Annotating and searching web tables using entities, types and relationships
Girija Limaye, Sunita Sarawagi, and Soumen Chakrabarti. 2010 · 2010
Earlier work this paper cites.
Structure-aware pre-training for table understanding with tree-based transformers
Zhiruo Wang, Haoyu Dong, Ran Jia, Jia Li, Zhiyi Fu, Shi Han, and Dongmei Zhang. 2020 · 2010
Earlier work this paper cites.
Recovering semantics of tables on the web
Petros Venetis, Alon Halevy, Jayant Madhavan, Marius Paşca, Warren Shen, Fei Wu, Gengxin Miao, and Chung Wu. 2011 · 2011
Earlier work this paper cites.
Finding related tables
Anish Das Sarma, Lujun Fang, Nitin Gupta, Alon Halevy, Hongrae Lee, Fei Wu, Reynold Xin, and Cong Yu. 2012 · 2012
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba. 2015 · 2015
Cited alongside, same era.
Compositional semantic parsing on semi-structured tables
Panupong Pasupat and Percy Liang. 2015 · 2015
Cited alongside, same era.
Billion-scale similarity search with gpus
Jeff Johnson, Matthijs Douze, and Hervé Jégou. 2017 · 2017
Cited alongside, same era.
Understanding the semantic structures of tables with a hybrid deep neural network architecture
Kyosuke Nishida, Kugatsu Sadamitsu, Ryuichiro Higashinaka, and Yoshihiro Matsuo. 2017 · 2017
Cited alongside, same era.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, ¥L ukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Cited alongside, same era.
Entitables: Smart assistance for entity-focused tables
Sherlock: A deep learning approach to semantic data type detection
M. Hulsebos, K. Hu, M. Bakker, Emanuel Zgraggen, Arvind Satyanarayan, T. Kraska, cCaugatay Demiralp, and C’esar A. Hidalgo. 2019 · 2019
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Deep splitting and merging for table structure decomposition
C. Tensmeyer, V. I. Morariu, B. Price, S. Cohen, and T. Martinez. 2019 · 2019
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Do NLP models know numbers? probing numeracy in embeddings
Eric Wallace, Yizhong Wang, Sujian Li, Sameer Singh, and Matt Gardner. 2019 · 2019
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Sato: Contextual semantic type detection in tables
Dan Zhang, Yoshihiko Suhara, Jinfeng Li, Madelon Hulsebos, Çağatay Demiralp, and Wang-Chiew Tan. 2019 · 2019
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Electra: Pre-training text encoders as discriminators rather than generators
Kevin Clark, Minh-Thang Luong, Quoc V. Le, and Christopher D. Manning. 2020 · 2020
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Shuo Zhang and Krisztian Balog. 2017 · 2017
Cited alongside, same era.
Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018 · 2018
Cited alongside, same era.
Memory augmented policy optimization for program synthesis and semantic parsing
Chen Liang, Mohammad Norouzi, Jonathan Berant, Quoc Le, and Ni Lao. 2018 · 2018
Cited alongside, same era.
Exploring the limits of weakly supervised pretraining
D. Mahajan, Ross B. Girshick, Vignesh Ramanathan, Kaiming He, Manohar Paluri, Y. Li, Ashwin Bharambe, and L. V. D. Maaten. 2018 · 2018
Cited alongside, same era.
Deep contextualized word representations
Matthew E. Peters, Mark Neumann, Mohit Iyyer, Matt Gardner, Christopher Clark, Kenton Lee, and Luke Zettlemoyer. 2018 · 2018
Cited alongside, same era.
Table2vec: Neural word and entity embeddings for table population and retrieval
Li Deng, Shuo Zhang, and Krisztian Balog. 2019 · 2019
Cited alongside, same era.
Viznet: Towards A large-scale visualization learning and benchmarking repository
Kevin Zeng Hu, Snehalkumar (Neil) S. Gaikwad, Madelon Hulsebos, Michiel A. Bakker, Emanuel Zgraggen, César A. Hidalgo, Tim Kraska, Guoliang Li, Arvind Satyanarayan, and Çagatay Demiralp. 2019 · 2019
Cited alongside, same era.
Turl: Table understanding through representation learning
Xiang Deng, Huan Sun, Alyssa Lees, You Wu, and Cong Yu. 2020 · 2020
Later among the works it cites.
Tapas: Weakly supervised table parsing via pre-training
Jonathan Herzig, P. Nowak, Thomas Müller, Francesco Piccinno, and Julian Martin Eisenschlos. 2020 · 2020
Later among the works it cites.
Table structure recognition using top-down and bottom-up cues
Sachin Raja, Ajoy Mondal, and C. V. Jawahar. 2020 · 2020
Later among the works it cites.
TaBERT: Pretraining for joint understanding of textual and tabular data
Pengcheng Yin, Graham Neubig, Wen tau Yih, and Sebastian Riedel. 2020 · 2020
Later among the works it cites.
Web table extraction, retrieval, and augmentation: A survey
Shuo Zhang and Krisztian Balog. 2020 · 2020
Later among the works it cites.
Novel entity discovery from web tables
Shuo Zhang, Edgar Meij, Krisztian Balog, and Ridho Reinanda. 2020 · 2020
Later among the works it cites.
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 · 2021
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