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Recently, Large Language Models (LLMs) have been demonstrated to possess impressive capabilities in a variety of domains and tasks.
CoSQL: A conversational text-to-SQL challenge towards cross-domain natural language interfaces to databases
Tao Yu, Rui Zhang, Heyang Er, Suyi Li, Eric Xue, Bo Pang, Xi Victoria Lin, Yi Chern Tan, Tianze Shi, Zihan Li, Youxuan Jiang, Michihiro Yasunaga, Sungrok Shim, Tao Chen, Alexander Fabbri, Zifan Li, Luyao Chen, Yuwen Zhang, Shreya Dixit, Vincent Zhang, Caiming Xiong, Richard Socher, Walter Lasecki, and Dragomir Radev. 2019a · 1979
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Natural language interfaces to databases-an introduction
Ion Androutsopoulos, Graeme D Ritchie, and Peter Thanisch. 1995 · 1995
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Sqlnet: Generating structured queries from natural language without reinforcement learning
Xiaojun Xu, Chang Liu, and Dawn Song. 2017 · 2017
Earlier work this paper cites.
Seq2sql: Generating structured queries from natural language using reinforcement learning
Victor Zhong, Caiming Xiong, and Richard Socher. 2017 · 2017
Earlier work this paper cites.
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 · 2019
Earlier work this paper cites.
Language models are few-shot learners
Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020 · 2020
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IGSQL: Database schema interaction graph based neural model for context-dependent text-to-SQL generation
Yitao Cai and Xiaojun Wan. 2020 · 2020
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Tracking interaction states for multi-turn text-to-sql semantic parsing
Run-Ze Wang, Zhen-Hua Ling, Jing-Bo Zhou, and Yu Hu. 2020 · 2020
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Grounded adaptation for zero-shot executable semantic parsing
Victor Zhong, Mike Lewis, Sida I. Wang, and Luke Zettlemoyer. 2020 · 2020
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Decoupled dialogue modeling and semantic parsing for multi-turn text-to-sql
Zhi Chen, Lu Chen, Hanqi Li, Ruisheng Cao, Da Ma, Mengyue Wu, and Kai Yu. 2021b · 2021
Cited alongside, same era.
Dynamic hybrid relation network for cross-domain context-dependent semantic parsing
Binyuan Hui, Ruiying Geng, Qiyu Ren, Binhua Li, Yongbin Li, Jian Sun, Fei Huang, Luo Si, Pengfei Zhu, and Xiaodan Zhu. 2021 · 2021
Cited alongside, same era.
PICARD: Parsing incrementally for constrained auto-regressive decoding from language models
Torsten Scholak, Nathan Schucher, and Dzmitry Bahdanau. 2021 · 2021
Cited alongside, same era.
Star: Sql guided pre-training for context-dependent text-to-sql parsing
Zefeng Cai, Xiangyu Li, Binyuan Hui, Min Yang, Bowen Li, Binhua Li, Zheng Cao, Weijie Li, Fei Huang, Luo Si, et al. 2022 · 2022
Cited alongside, same era.
Training language models to follow instructions with human feedback
Long Ouyang, Jeff Wu, Xu Jiang, Diogo Almeida, Carroll L. Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, John Schulman, Jacob Hilton, Fraser Kelton, Luke Miller, Maddie Simens, Amanda Askell, Peter Welinder, Paul Christiano, Jan Leike, and Ryan Lowe. 2022 · 2022
HIE-SQL: History information enhanced network for context-dependent text-to-SQL semantic parsing
Yanzhao Zheng, Haibin Wang, Baohua Dong, Xingjun Wang, and Changshan Li. 2022 · 2022
Later among the works it cites.
Linyong Nan, Yilun Zhao, Weijin Zou, Narutatsu Ri, Jaesung Tae, Ellen Zhang, Arman Cohan, and Dragomir Radev. 2023 · 2023
Later among the works it cites.
Din-sql: Decomposed in-context learning of text-to-sql with self-correction
Mohammadreza Pourreza and Davood Rafiei. 2023 · 2023
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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. 2023 · 2023
Later among the works it cites.
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Cited alongside, same era.
RASAT: Integrating relational structures into pretrained Seq2Seq model for text-to-SQL
Jiexing Qi, Jingyao Tang, Ziwei He, Xiangpeng Wan, Yu Cheng, Chenghu Zhou, Xinbing Wang, Quanshi Zhang, and Zhouhan Lin. 2022 · 2022
Cited alongside, same era.
Evaluating the text-to-sql capabilities of large language models
Nitarshan Rajkumar, Raymond Li, and Dzmitry Bahdanau. 2022 · 2022
Cited alongside, same era.
React: Synergizing reasoning and acting in language models
Shunyu Yao, Jeffrey Zhao, Dian Yu, Izhak Shafran, Karthik R Narasimhan, and Yuan Cao. 2022 · 2022
Cited alongside, same era.
Evaluating large language models trained on code
Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Ponde de Oliveira Pinto, Jared Kaplan, Harri Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, Alex Ray, Raul Puri, Gretchen Krueger, Michael Petrov, Heidy Khlaaf, Girish Sastry, Pamela Mishkin, Brooke Chan, Scott Gray, Nick Ryder, Mikhail Pavlov, Alethea Power, Lukasz Kaiser, Mohammad Bavarian, Clemens Winter, Philippe Tillet, Felipe Petroski Such, Dave Cummings, Matthias Plappert, Fotios Chantzis, Elizabeth Barnes, Ariel Herbert-Voss, William Hebgen Guss, Alex Nichol, Alex Paino, Nikolas Tezak, Jie Tang, Igor Babuschkin, Suchir Balaji, Shantanu Jain, William Saunders, Christopher Hesse, Andrew N. Carr, Jan Leike, Josh Achiam, Vedant Misra, Evan Morikawa, Alec Radford, Matthew Knight, Miles Brundage, Mira Murati, Katie Mayer, Peter Welinder, Bob McGrew, Dario Amodei, Sam McCandlish, Ilya Sutskever, and Wojciech Zaremba. 2021a
Cited in the paper.
Teaching large language models to self-debug
Xinyun Chen, Maxwell Lin, Nathanael Schärli, and Denny Zhou. 2023a
Cited in the paper.
Text-to-sql error correction with language models of code
Ziru Chen, Shijie Chen, Michael White, Raymond Mooney, Ali Payani, Jayanth Srinivasa, Yu Su, and Huan Sun. 2023b
Cited in the paper.
SParC: Cross-domain semantic parsing in context
Tao Yu, Rui Zhang, Michihiro Yasunaga, Yi Chern Tan, Xi Victoria Lin, Suyi Li, Heyang Er, Irene Li, Bo Pang, Tao Chen, Emily Ji, Shreya Dixit, David Proctor, Sungrok Shim, Jonathan Kraft, Vincent Zhang, Caiming Xiong, Richard Socher, and Dragomir Radev. 2019b
Cited in the paper.
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin. 2023 · 2023
Later among the works it cites.
Chain-of-thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Brian Ichter, Fei Xia, Ed Chi, Quoc Le, and Denny Zhou. 2023 · 2023
Later among the works it cites.
Act-sql: In-context learning for text-to-sql with automatically-generated chain-of-thought
Hanchong Zhang, Ruisheng Cao, Lu Chen, Hongshen Xu, and Kai Yu. 2023 · 2023
Later among the works it cites.
Cqr-sql: Conversational question reformulation enhanced context-dependent text-to-sql parsers
Dongling Xiao, LinZheng Chai, Qian-Wen Zhang, Zhao Yan, Zhoujun Li, and Yunbo Cao. 2022 · 2068
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