Fetching the paper…
Reading the bibliography…
In Natural Language Interfaces to Databases systems, the text-to-SQL technique allows users to query databases by using natural language questions.
Scaling multi-domain dialogue state tracking via query reformulation
Pushpendre Rastogi, Arpit Gupta, Tongfei Chen, and Lambert Mathias. 2019 · 1903
Earlier work this paper cites.
X-SQL: reinforce schema representation with context
Pengcheng He, Yi Mao, Kaushik Chakrabarti, and Weizhu Chen. 2019a · 1908
Earlier work this paper cites.
NLTK: the natural language toolkit
Edward Loper and Steven Bird. 2002 · 2002
Earlier work this paper cites.
Seq2SQL: Generating structured queries from natural language using reinforcement learning
Victor Zhong, Caiming Xiong, and Richard Socher. 2017 · 2011
Earlier work this paper cites.
Semantic parsing on Freebase from question-answer pairs
Jonathan Berant, Andrew Chou, Roy Frostig, and Percy Liang. 2013 · 2013
Earlier work this paper cites.
Semantic technologies in IBM Watson
Alfio Gliozzo, Or Biran, Siddharth Patwardhan, and Kathleen McKeown. 2013 · 2013
Earlier work this paper cites.
Systems and methods for performing record actions in a multi-tenant database and application system
Sanjaya Lai, Kedar Doshi, Yamuna Esaiarasan, and Chaitanya Bhatt. 2014 · 2014
Earlier work this paper cites.
Constructing an interactive natural language interface for relational databases
Fei Li and HV Jagadish. 2014 · 2014
Earlier work this paper cites.
GloVe: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher D. Manning. 2014 · 2014
Earlier work this paper cites.
Datatone: Managing ambiguity in natural language interfaces for data visualization
Tong Gao, Mira Dontcheva, Eytan Adar, Zhicheng Liu, and Karrie G Karahalios. 2015 · 2015
Earlier work this paper cites.
Contrastive unsupervised word alignment with non-local features
Yang Liu and Maosong Sun. 2015 · 2015
Cited alongside, same era.
Language to logical form with neural attention
Li Dong and Mirella Lapata. 2016 · 2016
Cited alongside, same era.
Neural network-based word alignment through score aggregation
Joël Legrand, Michael Auli, and Ronan Collobert. 2016 · 2016
Cited alongside, same era.
Learning structured natural language representations for semantic parsing
Jianpeng Cheng, Siva Reddy, Vijay Saraswat, and Mirella Lapata. 2017 · 2017
Cited alongside, same era.
Analyza: Exploring data with conversation
Kedar Dhamdhere, Kevin S McCurley, Ralfi Nahmias, Mukund Sundararajan, and Qiqi Yan. 2017 · 2017
Cited alongside, same era.
Learning a neural semantic parser from user feedback
Srinivasan Iyer, Ioannis Konstas, Alvin Cheung, Jayant Krishnamurthy, and Luke Zettlemoyer. 2017 · 2017
Weakly-supervised semantic parsing with abstract examples
Omer Goldman, Veronica Latcinnik, Udi Naveh, Amir Globerson, and Jonathan Berant. 2018 · 2018
Later among the works it cites.
Question generation from SQL queries improves neural semantic parsing
Daya Guo, Yibo Sun, Duyu Tang, Nan Duan, Jian Yin, Hong Chi, James Cao, Peng Chen, and Ming Zhou. 2018 · 2018
Later among the works it cites.
DialSQL: Dialogue based structured query generation
Izzeddin Gur, Semih Yavuz, Yu Su, and Xifeng Yan. 2018 · 2018
Later among the works it cites.
Learning out-of-vocabulary words in intelligent personal agents
Avik Ray, Yilin Shen, and Hongxia Jin. 2018 · 2018
Later among the works it cites.
Natural language interfaces with fine-grained user interaction: A case study on web APIs
Yu Su, Ahmed Hassan Awadallah, Miaosen Wang, and Ryen W White. 2018 · 2018
Later among the works it cites.
BERT: Pre-training of deep bidirectional transformers for language understanding
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
SQLNet: Generating structured queries from natural language without reinforcement learning
Xiaojun Xu, Chang Liu, and Dawn Song. 2017 · 2017
Cited alongside, same era.
SQLizer: query synthesis from natural language
Navid Yaghmazadeh, Yuepeng Wang, Isil Dillig, and Thomas Dillig. 2017 · 2017
Cited alongside, same era.
Coarse-to-fine decoding for neural semantic parsing
Li Dong and Mirella Lapata. 2018 · 2018
Cited alongside, same era.
Improving text-to-SQL evaluation methodology
Catherine Finegan-Dollak, Jonathan K Kummerfeld, Li Zhang, Karthik Ramanathan, Sesh Sadasivam, Rui Zhang, and Dragomir Radev. 2018 · 2018
Cited alongside, same era.
Global reasoning over database structures for text-to-SQL parsing
Ben Bogin, Matt Gardner, and Jonathan Berant. 2019a
Cited in the paper.
Representing schema structure with graph neural networks for text-to-SQL parsing
Ben Bogin, Matt Gardner, and Jonathan Berant. 2019b
Cited in the paper.
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Later among the works it cites.
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 · 2019
Later among the works it cites.
A comprehensive exploration on WikiSQL with table-aware word contextualization
Wonseok Hwang, Jinyeung Yim, Seunghyun Park, and Minjoon Seo. 2019 · 2019
Later among the works it cites.
Model-based interactive semantic parsing: A unified framework and a text-to-SQL case study
Ziyu Yao, Yu Su, Huan Sun, and Wen-tau Yih. 2019 · 2019
Later among the works it cites.
How far are we from effective context modeling? an exploratory study on semantic parsing in context twitter
Qian Liu, Bei Chen, Jiaqi Guo, Jian-Guang Lou, Bin Zhou, and Dongmei Zhang. 2020 · 2020
Closest in time.