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Recently, there has been increasing interest in synthesizing data to improve downstream text-to-SQL tasks.
Learning to Parse Database Queries Using Inductive Logic Programming
Zelle, J. M.; and Mooney, R. J. 1996 · 1996
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Automated Construction of Database Interfaces: Intergrating Statistical and Relational Learning for Semantic Parsing
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Bleu: a Method for Automatic Evaluation of Machine Translation
Papineni, K.; Roukos, S.; Ward, T.; and Zhu, W.-J. 2002 · 2002
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Towards a Theory of Natural Language Interfaces to Databases
Popescu, A.-M.; Etzioni, O.; and Kautz, H. 2003 · 2003
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ROUGE: A Package for Automatic Evaluation of Summaries
Lin, C.-Y. 2004 · 2004
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Constructing an Interactive Natural Language Interface for Relational Databases
Li, F.; and Jagadish, H. V. 2014 · 2014
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TabEL: Entity Linking in Web Tables
Bhagavatula, C.; Noraset, T.; and Downey, D. 2015 · 2015
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Data Recombination for Neural Semantic Parsing
Jia, R.; and Liang, P. 2016 · 2016
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Learning a Neural Semantic Parser from User Feedback
Iyer, S.; Konstas, I.; Cheung, A.; Krishnamurthy, J.; and Zettlemoyer, L. 2017 · 2017
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Type- and Content-Driven Synthesis of SQL Queries from Natural Language
Yaghmazadeh, N.; Wang, Y.; Dillig, I.; and Dillig, T. 2017 · 2017
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Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning
Zhong, V.; Xiong, C.; and Socher, R. 2017 · 2017
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Question Generation from SQL Queries Improves Neural Semantic Parsing
Guo, D.; Sun, Y.; Tang, D.; Duan, N.; Yin, J.; Chi, H.; Cao, J.; Chen, P.; and Zhou, M. 2018 · 2018
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SyntaxSQLNet: Syntax Tree Networks for Complex and Cross-Domain Text-to-SQL Task
Yu, T.; Yasunaga, M.; Yang, K.; Zhang, R.; Wang, D.; Li, Z.; and Radev, D. R. 2018a · 2018
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Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task
Yu, T.; Zhang, R.; Yang, K.; Yasunaga, M.; Wang, D.; Li, Z.; Ma, J.; Li, I.; Yao, Q.; Roman, S.; Zhang, Z.; and Radev, D. 2018b · 2018
Cited alongside, same era.
Towards Complex Text-to-SQL in Cross-Domain Database with Intermediate Representation
Guo, J.; Zhan, Z.; Gao, Y.; Xiao, Y.; Lou, J.; Liu, T.; and Zhang, D. 2019a · 2019
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Editing-Based SQL Query Generation for Cross-Domain Context-Dependent Questions
Zhang, R.; Yu, T.; Er, H.; Shim, S.; Xue, E.; Lin, X. V.; Shi, T.; Xiong, C.; Socher, R.; and Radev, D. 2019 · 2019
Cited alongside, same era.
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
Raffel, C.; Shazeer, N.; Roberts, A.; Lee, K.; Narang, S.; Matena, M.; Zhou, Y.; Li, W.; and Liu, P. J. 2020 · 2020
Cited alongside, same era.
SmBoP: Semi-autoregressive Bottom-up Semantic Parsing
Rubin, O.; and Berant, J. 2021 · 2021
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PICARD: Parsing Incrementally for Constrained Auto-Regressive Decoding from Language Models
Scholak, T.; Schucher, N.; and Bahdanau, D. 2021 · 2021
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Compositional Generalization and Natural Language Variation: Can a Semantic Parsing Approach Handle Both?
Shaw, P.; Chang, M.-W.; Pasupat, P.; and Toutanova, K. 2021 · 2021
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Learning contextual representations for semantic parsing with generation-augmented pre-training
Shi, P.; Ng, P.; Wang, Z.; Zhu, H.; Li, A. H.; Wang, J.; dos Santos, C. N.; and Xiang, B. 2021 · 2021
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Learning to Synthesize Data for Semantic Parsing
Wang, B.; Yin, W.; Lin, X. V.; and Xiong, C. 2021 · 2021
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On the Potential of Lexico-logical Alignments for Semantic Parsing to SQL Queries
Shi, T.; Zhao, C.; Boyd-Graber, J.; Daumé III, H.; and Lee, L. 2020 · 2020
Cited alongside, same era.
RAT-SQL: Relation-Aware Schema Encoding and Linking for Text-to-SQL Parsers
Wang, B.; Shin, R.; Liu, X.; Polozov, O.; and Richardson, M. 2020 · 2020
Cited alongside, same era.
BERTScore: Evaluating Text Generation with BERT
Zhang*, T.; Kishore*, V.; Wu*, F.; Weinberger, K. Q.; and Artzi, Y. 2020 · 2020
Cited alongside, same era.
Grounded Adaptation for Zero-shot Executable Semantic Parsing
Zhong, V.; Lewis, M.; Wang, S. I.; and Zettlemoyer, L. 2020 · 2020
Cited alongside, same era.
LGESQL: Line Graph Enhanced Text-to-SQL Model with Mixed Local and Non-Local Relations
Cao, R.; Chen, L.; Chen, Z.; Zhao, Y.; Zhu, S.; and Yu, K. 2021 · 2021
Cited alongside, same era.
Natural SQL: Making SQL Easier to Infer from Natural Language Specifications
Gan, Y.; Chen, X.; Xie, J.; Purver, M.; Woodward, J. R.; Drake, J.; and Zhang, Q. 2021a · 2021
Cited alongside, same era.
GitTables: A Large-Scale Corpus of Relational Tables
Hulsebos, M.; Demiralp, Ç.; and Groth, P. 2021 · 2021
Cited alongside, same era.
Wu, K.; Wang, L.; Li, Z.; Zhang, A.; Xiao, X.; Wu, H.; Zhang, M.; and Wang, H. 2021 · 2021
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Optimizing Deeper Transformers on Small Datasets
Xu, P.; Kumar, D.; Yang, W.; Zi, W.; Tang, K.; Huang, C.; Cheung, J. C. K.; Prince, S. J.; and Cao, Y. 2021 · 2021
Later among the works it cites.
Hierarchical Neural Data Synthesis for Semantic Parsing
Yang, W.; Xu, P.; and Cao, Y. 2021 · 2021
Later among the works it cites.
GraPPa: Grammar-Augmented Pre-Training for Table Semantic Parsing
Yu, T.; Wu, C.-S.; Lin, X. V.; Wang, B.; Tan, Y. C.; Yang, X.; Radev, D.; Socher, R.; and Xiong, C. 2021 · 2021
Later among the works it cites.
S 2 SQL: Injecting Syntax to Question-Schema Interaction Graph Encoder for Text-to-SQL Parsers
Hui, B.; Geng, R.; Wang, L.; Qin, B.; Li, Y.; Li, B.; Sun, J.; and Li, Y. 2022 · 2022
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RASAT: Integrating Relational Structures into Pretrained Seq2Seq Model for Text-to-SQL
Qi, J.; Tang, J.; He, Z.; Wan, X.; Zhou, C.; Wang, X.; Zhang, Q.; and Lin, Z. 2022 · 2022
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Xie, T.; Wu, C. H.; Shi, P.; Zhong, R.; Scholak, T.; Yasunaga, M.; Wu, C.-S.; Zhong, M.; Yin, P.; Wang, S. I.; Zhong, V.; Wang, B.; Li, C.; Boyle, C.; Ni, A.; Yao, Z.; Radev, D.; Xiong, C.; Kong, L.; Zhang, R.; Smith, N. A.; Zettlemoyer, L.; and Yu, T. 2022 · 2022
Closest in time.