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Multi-task deep neural networks for natural language understanding
Original
Xiaodong Liu, Pengcheng He, Weizhu Chen, and Jianfeng Gao · 1901
Earlier work this paper cites.
A comprehensive exploration on wikisql with table-aware word contextualization
Original
Wonseok Hwang, Jinyeung Yim, Seunghyun Park, and Minjoon Seo · 1902
Earlier work this paper cites.
Towards complex text-to-sql in cross-domain database with intermediate representation
Original
Jiaqi Guo, Zecheng Zhan, Yan Gao, Yan Xiao, Jian-Guang Lou, Ting Liu, and Dongmei Zhang · 1905
Earlier work this paper cites.
Roberta: A robustly optimized bert pretraining approach
Original
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov · 1907
Earlier work this paper cites.
X-sql: Reinforce context into schema representation
Original
Pengcheng He, Yi Mao, Kaushik Chakrabarti, and Weizhu Chen · 1908
Earlier work this paper cites.
Natural language interfaces to databases–an introduction
Ion Androutsopoulos, Graeme D. Ritchie, and Peter Thanisch · 1995
Earlier work this paper cites.

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Reading the bibliography…

2020

Lyu, Qin, Chakrabarti, Kaushik, Hathi, Shobhit et al.

In this paper, we study how to leverage pre-trained language models in Text-to-SQL.

We argue that previous approaches under utilize the base language models by concatenating all columns together with the NL question and feeding them into the base language model in the encoding stage.
We propose a neat approach called Hybrid Ranking Network (HydraNet) which breaks down the problem into column-wise ranking and decoding and finally assembles the column-wise outputs into a SQL query by straightforward rules.
In this approach, the encoder is given a NL question and one individual column, which perfectly aligns with the original tasks BERT/RoBERTa is trained on, and hence we avoid any ad-hoc pooling or additional encoding layers which are necessary in prior approaches.

Multi-task deep neural networks for natural language understanding
Original
Xiaodong Liu, Pengcheng He, Weizhu Chen, and Jianfeng Gao · 1901
Earlier work this paper cites.
A comprehensive exploration on wikisql with table-aware word contextualization
Original
Wonseok Hwang, Jinyeung Yim, Seunghyun Park, and Minjoon Seo · 1902
Earlier work this paper cites.
Towards complex text-to-sql in cross-domain database with intermediate representation
Original
Jiaqi Guo, Zecheng Zhan, Yan Gao, Yan Xiao, Jian-Guang Lou, Ting Liu, and Dongmei Zhang · 1905
Earlier work this paper cites.
Roberta: A robustly optimized bert pretraining approach
Original
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov · 1907
Earlier work this paper cites.
X-sql: Reinforce context into schema representation
Original
Pengcheng He, Yi Mao, Kaushik Chakrabarti, and Weizhu Chen · 1908
Earlier work this paper cites.
Natural language interfaces to databases–an introduction
Ion Androutsopoulos, Graeme D. Ritchie, and Peter Thanisch · 1995
Earlier work this paper cites.

Towards a theory of natural language interfaces to databases
Ana-Maria Popescu, Oren Etzioni, and Henry Kautz · 2003
Cited alongside, same era.
Seq2SQL: Generating structured queries from natural language using reinforcement learning
Original
Victor Zhong, Caiming Xiong, and Richard Socher · 2008
Cited alongside, same era.
SQLNet: Generating structured queries from natural language without reinforcement learning
Original
Xiaojun Xu, Chang Liu, and Dawn Song · 2017
Cited alongside, same era.
Bert: Pre-training of deep bidirectional transformers for language understanding
Original
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
Cited alongside, same era.
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Li Dong and Mirella Lapata · 2018
Cited alongside, same era.

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Chenglong Wang, Po-Sen Huang, Oleksandr Polozov, Marc Brockschmidt, and Rishabh Singh · 2018
Later among the works it cites.
TypeSQL: Knowledge-based type-aware neural text-to-SQL generation
Tao Yu, Zifan Li, Zilin Zhang, Rui Zhang, and Dragomir Radev · 2018
Later among the works it cites.
A comparative survey of recent natural language interfaces for databases
Katrin Affolter, Kurt Stockinger, and Abraham Bernstein · 2019
Later among the works it cites.
Zero-shot text-to-sql learning with auxiliary task
Original
Shuaichen Chang, Pengfei Liu, Yun Tang, Jing Huang, Xiaodong He, and Bowen Zhou · 2019
Later among the works it cites.
Understanding the behaviors of bert in ranking
Original
Yifan Qiao, Chenyan Xiong, Zhenghao Liu, and Zhiyuan Liu · 2019
Later among the works it cites.

alphaXiv searches the wider corpus for related work and actual follow-ups.

alphaXiv is searching for related work…

Tianze Shi, Kedar Tatwawadi, Kaushik Chakrabarti, Yi Mao, Oleksandr Polozov, and Weizhu Chen · 2018

Cited alongside, same era.

Xlnet: Generalized autoregressive pretraining for language understanding

Zhilin Yang, Zihang Dai, Yiming Yang, Jaime Carbonell, Russ R Salakhutdinov, and Quoc V Le · 2019

Later among the works it cites.