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The Text-to-SQL task, aiming to translate the natural language of the questions into SQL queries, has drawn much attention recently.
Expanding the scope of the ATIS task: The ATIS-3 corpus
Deborah A. Dahl, Madeleine Bates, Michael Brown, William Fisher, Kate Hunicke-Smith, David Pallett, Christine Pao, Alexander Rudnicky, and Elizabeth Shriberg · 1994
Earlier work this paper cites.
Learning to parse database queries using inductive logic programming
John M Zelle and Raymond J Mooney · 1996
Earlier work this paper cites.
Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
Earlier work this paper cites.
Learning phrase representations using RNN encoder–decoder for statistical machine translation
Kyunghyun Cho, Bart van Merriënboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio · 2014
Earlier work this paper cites.
The Stanford CoreNLP natural language processing toolkit
Christopher Manning, Mihai Surdeanu, John Bauer, Jenny Finkel, Steven Bethard, and David McClosky · 2014
Earlier work this paper cites.
GloVe: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher Manning · 2014
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba · 2015
Earlier work this paper cites.
Jimmy Lei Ba, Jamie Ryan Kiros, and Geoffrey E Hinton · 2016
Earlier work this paper cites.
Gated graph sequence neural networks
Yujia Li, Daniel Tarlow, Marc Brockschmidt, and Richard S. Zemel · 2016
Earlier work this paper cites.
Seq2sql: Generating structured queries from natural language using reinforcement learning
Victor Zhong an · 2017
Earlier work this paper cites.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin · 2017
Earlier work this paper cites.
Sqlnet: Generating structured queries from natural language without reinforcement learning
Xiaojun Xu, Chang Liu, and Dawn Song · 2017
Earlier work this paper cites.
Sqlizer: query synthesis from natural language
Navid Yaghmazadeh, Yuepeng Wang, Isil Dillig, and Thomas Dillig · 2017
Earlier work this paper cites.
A syntactic neural model for general-purpose code generation
Pengcheng Yin and Graham Neubig · 2017
Cited alongside, same era.
Graph-to-sequence learning using gated graph neural networks
Daniel Beck, Gholamreza Haffari, and Trevor Cohn · 2018
Cited alongside, same era.
An encoder-decoder framework translating natural language to database queries
Ruichu Cai, Boyan Xu, Zhenjie Zhang, Xiaoyan Yang, Zijian Li, and Zhihao Liang · 2018
Cited alongside, same era.
TypeSQL: Knowledge-based type-aware neural text-to-SQL generation
Tao Yu, Zifan Li, Zilin Zhang, Rui Zhang, and Dragomir Radev · 2018
Cited alongside, same era.
Spider: A large-scale human-labeled dataset for complex and cross-domain semantic parsing and text-to-SQL task
Tao Yu, Rui Zhang, Kai Yang, Michihiro Yasunaga, Dongxu Wang, Zifan Li, James Ma, Irene Li, Qingning Yao, Shanelle Roman, Zilin Zhang, and Dragomir Radev · 2018
Cited alongside, same era.
Bridging textual and tabular data for cross-domain text-to-SQL semantic parsing
Xi Victoria Lin, Richard Socher, and Caiming Xiong · 2020
Later among the works it cites.
RAT-SQL: Relation-aware schema encoding and linking for text-to-SQL parsers
Bailin Wang, Richard Shin, Xiaodong Liu, Oleksandr Polozov, and Matthew Richardson · 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
Later among the works it cites.
Comprehensive information integration modeling framework for video titling
Shengyu Zhang, Ziqi Tan, Zhou Zhao, Jin Yu, Kun Kuang, Tan Jiang, Jingren Zhou, Hongxia Yang, and Fei Wu · 2020
Later among the works it cites.
LGESQL: Line graph enhanced text-to-SQL model with mixed local and non-local relations
Ruisheng Cao, Lu Chen, Zhi Chen, Yanbin Zhao, Su Zhu, and Kai Yu · 2021
Closest in time.
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Ben Bogin, Matt Gardner, and Jonathan Berant · 2019
Cited alongside, same era.
BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2019
Cited alongside, same era.
Towards complex text-to-SQL in cross-domain database with intermediate representation
Jiaqi Guo, Zecheng Zhan, Yan Gao, Yan Xiao, Jian-Guang Lou, Ting Liu, and Dongmei Zhang · 2019
Cited alongside, same era.
A comprehensive exploration on wikisql with table-aware word contextualization
Wonseok Hwang, Jinyeong Yim, Seunghyun Park, and Minjoon Seo · 2019
Cited alongside, same era.
Editing-based SQL query generation for cross-domain context-dependent questions
Rui Zhang, Tao Yu, Heyang Er, Sungrok Shim, Eric Xue, Xi Victoria Lin, Tianze Shi, Caiming Xiong, Richard Socher, and Dragomir Radev · 2019
Cited alongside, same era.
TaPas: Weakly supervised table parsing via pre-training
Jonathan Herzig, Pawel Krzysztof Nowak, Thomas Müller, Francesco Piccinno, and Julian Eisenschlos · 2020
Cited alongside, same era.
Bertrand-dr: Improving text-to-sql using a discriminative re-ranker
Amol Kelkar, Rohan Relan, Vaishali Bhardwaj, Saurabh Vaichal, Chandra Khatri, and Peter Relan · 2020
Cited alongside, same era.
ShadowGNN: Graph projection neural network for text-to-SQL parser
Zhi Chen, Lu Chen, Yanbin Zhao, Ruisheng Cao, Zihan Xu, Su Zhu, and Kai Yu · 2021
Closest in time.
Structure-grounded pretraining for text-to-SQL
Xiang Deng, Ahmed Hassan Awadallah, Christopher Meek, Oleksandr Polozov, Huan Sun, and Matthew Richardson · 2021
Closest in time.
SmBoP: Semi-autoregressive bottom-up semantic parsing
Ohad Rubin and Jonathan Berant · 2021
Closest in time.
DuoRAT: Towards simpler text-to-SQL models
Torsten Scholak, Raymond Li, Dzmitry Bahdanau, Harm de Vries, and Chris Pal · 2021
Closest in time.
Picard - parsing incrementally for constrained auto-regressive decoding from language models
Torsten Scholak, Nathan Schucher, and Dzmitry Bahdanau · 2021
Closest in time.
Learning contextual representations for semantic parsing with generation-augmented pre-training
Peng Shi, Patrick Ng, Zhiguo Wang, Henghui Zhu, Alexander Hanbo Li, Jun Wang, Cicero Nogueira dos Santos, and Bing Xiang · 2021
Closest in time.
Optimizing deeper transformers on small datasets
Peng Xu, Dhruv Kumar, Wei Yang, Wenjie Zi, Keyi Tang, Chenyang Huang, Jackie Chi Kit Cheung, Simon J.D. Prince, and Yanshuai Cao · 2021
Closest in time.
Grappa: Grammar-augmented pre-training for table semantic parsing
Tao Yu, Chien-Sheng Wu, Xi Victoria Lin, Yi Chern Tan, Xinyi Yang, Dragomir Radev, Caiming Xiong, et al · 2021
Closest in time.