Fetching the paper…
Reading the bibliography…
Tables are widely used with various structures to organize and present data.
An automated approach for retrieving hierarchical data from html tables
Seung-Jin Lim and Yiu-Kai Ng · 1999
Earlier work this paper cites.
A survey of table recognition
Richard Zanibbi, Dorothea Blostein, and James R Cordy · 2004
Earlier work this paper cites.
Web-scale table census and classification
Eric Crestan and Patrick Pantel · 2011
Earlier work this paper cites.
Table header detection and classification
Jing Fang, Prasenjit Mitra, Zhi Tang, and C Lee Giles · 2012
Earlier work this paper cites.
Automatic web spreadsheet data extraction
Zhe Chen and Michael Cafarella · 2013
Earlier work this paper cites.
Web table taxonomy and formalization
Larissa R Lautert, Marcelo M Scheidt, and Carina F Dorneles · 2013
Earlier work this paper cites.
Integrating spreadsheet data via accurate and low-effort extraction
Zhe Chen and Michael Cafarella · 2014
Earlier work this paper cites.
Tabel: entity linking in web tables
Chandra Sekhar Bhagavatula, Thanapon Noraset, and Doug Downey · 2015
Earlier work this paper cites.
Building the dresden web table corpus: A classification approach
Julian Eberius, Katrin Braunschweig, and Others · 2015
Earlier work this paper cites.
Compositional semantic parsing on semi-structured tables
Panupong Pasupat and Percy Liang · 2015
Earlier work this paper cites.
A large public corpus of web tables containing time and context metadata
Oliver Lehmberg, Dominique Ritze, Robert Meusel, and Christian Bizer · 2016
Earlier work this paper cites.
Tabular abstraction, editing, and formatting
Xinxin Wang · 2016
Earlier work this paper cites.
Understanding the semantic structures of tables with a hybrid deep neural network architecture
Kyosuke Nishida, Kugatsu Sadamitsu, Ryuichiro Higashinaka, and Yoshihiro Matsuo · 2017
Earlier work this paper cites.
Matching web tables to dbpedia-a feature utility study
Dominique Ritze and Christian Bizer · 2017
Earlier work this paper cites.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
Earlier work this paper cites.
Graph attention networks
Petar Veličković, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Lio, and Yoshua Bengio · 2017
Earlier work this paper cites.
Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
Cited alongside, same era.
Expandable group identification in spreadsheets
Wensheng Dou, Shi Han, Liang Xu, Dongmei Zhang, and Jun Wei · 2018
Cited alongside, same era.
Tabvec: Table vectors for classification of web tables
Majid Ghasemi-Gol and Pedro Szekely · 2018
Cited alongside, same era.
Table recognition in spreadsheets via a graph representation
Elvis Koci, Maik Thiele, Wolfgang Lehner, and Oscar Romero · 2018
Cited alongside, same era.
Improving language understanding by generative pre-training, 2018
Alec Radford, Karthik Narasimhan, Tim Salimans, and Ilya Sutskever · 2018
Cited alongside, same era.
Spider: A large-scale human-labeled dataset for complex and cross-domain semantic parsing and text-to-sql task
Tree transformer: Integrating tree structures into self-attention
Yau-Shian Wang, Hung-Yi Lee, and Yun-Nung Chen · 2019
Later among the works it cites.
Table2vec: Neural word and entity embeddings for table population and retrieval
Li Zhang, Shuo Zhang, and Krisztian Balog · 2019
Later among the works it cites.
Auto-em: End-to-end fuzzy entity-matching using pre-trained deep models and transfer learning
Chen Zhao and Yeye He · 2019
Later among the works it cites.
Turl: Table understanding through representation learning
Xiang Deng, Huan Sun, Alyssa Lees, You Wu, and Cong Yu · 2020
Closest in time.
Neural formatting for spreadsheet tables
Haoyu Dong Dong, Jinyu Wang, Zhouyu Fu, Shi Han, and Dongmei Zhang · 2020
Closest in time.
Active learning for spreadsheet cell classification
Julius Gonsior, Josephine Rehak, Maik Thiele, Elvis Koci, Michael Günther, and Wolfgang Lehner · 2020
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Tao Yu, Rui Zhang, Kai Yang, Michihiro Yasunaga, Dongxu Wang, Zifan Li, James Ma, Irene Li, et al · 2018
Cited alongside, same era.
Colnet: Embedding the semantics of web tables for column type prediction
Jiaoyan Chen, Ernesto Jiménez-Ruiz, Ian Horrocks, and Charles Sutton · 2019
Cited alongside, same era.
Learning semantic annotations for tabular data
Jiaoyan Chen, Ernesto Jiménez-Ruiz, Ian Horrocks, and Charles Sutton · 2019
Cited alongside, same era.
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
Cited alongside, same era.
Semantic structure extraction for spreadsheet tables with a multi-task learning architecture
Haoyu Dong, Shijie Liu, Zhouyu Fu, Shi Han, and Dongmei Zhang · 2019
Cited alongside, same era.
Tablesense: Spreadsheet table detection with convolutional neural networks
Haoyu Dong, Shijie Liu, Shi Han, Zhouyu Fu, and Dongmei Zhang · 2019
Cited alongside, same era.
Tablenet: An approach for determining fine-grained relations for wikipedia tables
Besnik Fetahu, Avishek Anand, and Maria Koutraki · 2019
Cited alongside, same era.
Closest in time.
Web table column type detection using deep learning and probability graph model
Tong Guo, Derong Shen, Tiezheng Nie, and Yue Kou · 2020
Closest in time.
Tapas: Weakly supervised table parsing via pre-training
Jonathan Herzig, Paweł Krzysztof Nowak, Thomas Müller, Francesco Piccinno, and Julian Martin Eisenschlos · 2020
Closest in time.
Axcell: Automatic extraction of results from machine learning papers
Marcin Kardas, Piotr Czapla, Pontus Stenetorp, Sebastian Ruder, Sebastian Riedel, Ross Taylor, and Robert Stojnic · 2020
Closest in time.
Tree-structured attention with hierarchical accumulation
Xuan-Phi Nguyen, Shafiq Joty, Steven CH Hoi, and Richard Socher · 2020
Closest in time.
Table header correction algorithm based on heuristics for improving spreadsheet data extraction
Viacheslav Paramonov, Alexey Shigarov, and Varvara Vetrova · 2020
Closest in time.
Tabert: Pretraining for joint understanding of textual and tabular data
Pengcheng Yin, Graham Neubig, Wen-tau Yih, and Sebastian Riedel · 2020
Closest in time.
A graph representation of semi-structured data for web question answering
Xingyao Zhang, Linjun Shou, Jian Pei, Ming Gong, Lijie Wen, and Daxin Jiang · 2020
Closest in time.
Table2analysis: Modeling and recommendation of common analysis patterns for multi-dimensional data
Mengyu Zhou, Wang Tao, Ji Pengxin, and Others · 2020
Closest in time.
A hybrid probabilistic approach for table understanding
Kexuan Sun Harsha Rayudu Jay Pujara · 2021
Closest in time.
Representations for question answering from documents with tables and text
Vicky Zayats, Kristina Toutanova, and Mari Ostendorf · 2021
Closest in time.