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The robustness of Text-to-SQL parsers against adversarial perturbations plays a crucial role in delivering highly reliable applications.
A comprehensive exploration on wikisql with table-aware word contextualization
Wonseok Hwang, Jinyeong Yim, Seunghyun Park, and Minjoon Seo. 2019 · 1902
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Roberta: A robustly optimized BERT pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 1907
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Benchmarking zero-shot text classification: Datasets, evaluation and entailment approach
Wenpeng Yin, Jamaal Hay, and Dan Roth. 2019 · 1909
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Content enhanced bert-based text-to-sql generation
Tong Guo and Huilin Gao. 2019 · 1910
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Imperceptible adversarial attacks on tabular data
Vincent Ballet, Xavier Renard, Jonathan Aigrain, Thibault Laugel, Pascal Frossard, and Marcin Detyniecki. 2019 · 1911
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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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TAPAS: weakly supervised table parsing via pre-training
Jonathan Herzig, Pawel Krzysztof Nowak, Thomas Müller, Francesco Piccinno, and Julian Martin Eisenschlos. 2020 · 2004
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Fundamentals of relational database management systems , volume 47
Sai Sumathi and S Esakkirajan. 2007 · 2007
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Photon: A robust cross-domain text-to-sql system
Jichuan Zeng, Xi Victoria Lin, Caiming Xiong, Richard Socher, Michael R Lyu, Irwin King, and Steven CH Hoi. 2020 · 2007
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The Probabilistic Relevance Framework: BM25 and Beyond
S. Robertson. 2009 · 2009
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Recognizing Textual Entailment: Models and Applications
Ido Dagan, Dan Roth, Mark Sammons, and Fabio Massimo Zanzotto. 2013 · 2013
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Distributed representations of words and phrases and their compositionality
Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean. 2013 · 2013
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GloVe: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher Manning. 2014 · 2014
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A large annotated corpus for learning natural language inference
Samuel R. Bowman, Gabor Angeli, Christopher Potts, and Christopher D. Manning. 2015 · 2015
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Compositional semantic parsing on semi-structured tables
Panupong Pasupat and Percy Liang. 2015 · 2015
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From paraphrase database to compositional paraphrase model and back
John Wieting, Mohit Bansal, Kevin Gimpel, and Karen Livescu. 2015 · 2015
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A large public corpus of web tables containing time and context metadata
Oliver Lehmberg, Dominique Ritze, Robert Meusel, and Christian Bizer. 2016 · 2016
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Understanding natural language queries over relational databases
Fei Li and H. V. Jagadish. 2016 · 2016
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Counter-fitting word vectors to linguistic constraints
Nikola Mrkšić, Diarmuid Ó Séaghdha, Blaise Thomson, Milica Gašić, Lina M. Rojas-Barahona, Pei-Hao Su, David Vandyke, Tsung-Hsien Wen, and Steve Young. 2016 · 2016
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Counter-fitting word vectors to linguistic constraints
Nikola Mrksic, Diarmuid Ó Séaghdha, Blaise Thomson, Milica Gasic, Lina Maria Rojas-Barahona, Pei-Hao Su, David Vandyke, Tsung-Hsien Wen, and Steve J. Young. 2016 · 2016
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Practical black-box attacks against machine learning
Nicolas Papernot, Patrick McDaniel, Ian Goodfellow, Somesh Jha, Z Berkay Celik, and Ananthram Swami. 2017 · 2017
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ConceptNet 5.5: An open multilingual graph of general knowledge
Robyn Speer, Joshua Chin, and Catherine Havasi. 2017 · 2017
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Re-examining the role of schema linking in text-to-SQL
Wenqiang Lei, Weixin Wang, Zhixin Ma, Tian Gan, Wei Lu, Min-Yen Kan, and Tat-Seng Chua. 2020 · 2020
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BERT-ATTACK: Adversarial attack against BERT using BERT
Linyang Li, Ruotian Ma, Qipeng Guo, Xiangyang Xue, and Xipeng Qiu. 2020 · 2020
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Mt-teql: Evaluating and augmenting consistency of text-to-sql models with metamorphic testing
Pingchuan Ma and Shuai Wang. 2020 · 2020
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TextAttack: A framework for adversarial attacks, data augmentation, and adversarial training in NLP
John Morris, Eli Lifland, Jin Yong Yoo, Jake Grigsby, Di Jin, and Yanjun Qi. 2020 · 2020
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On the potential of lexico-logical alignments for semantic parsing to SQL queries
Tianze Shi, Chen Zhao, Jordan Boyd-Graber, Hal Daumé III, and Lillian Lee. 2020 · 2020
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Adina Williams, Nikita Nangia, and Samuel R. Bowman. 2017 · 2017
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Seq2sql: Generating structured queries from natural language using reinforcement learning
Victor Zhong, Caiming Xiong, and Richard Socher. 2017 · 2017
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Synthetic and natural noise both break neural machine translation
Yonatan Belinkov and Yonatan Bisk. 2018 · 2018
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Black-box generation of adversarial text sequences to evade deep learning classifiers
Ji Gao, Jack Lanchantin, Mary Lou Soffa, and Yanjun Qi. 2018 · 2018
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Adversarial example generation with syntactically controlled paraphrase networks
Mohit Iyyer, John Wieting, Kevin Gimpel, and Luke Zettlemoyer. 2018 · 2018
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Semantically equivalent adversarial rules for debugging NLP models
Marco Tulio Ribeiro, Sameer Singh, and Carlos Guestrin. 2018 · 2018
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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 · 2018
Cited alongside, same era.
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 · 2020
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Transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Remi Louf, Morgan Funtowicz, Joe Davison, Sam Shleifer, Patrick von Platen, Clara Ma, Yacine Jernite, Julien Plu, Canwen Xu, Teven Le Scao, Sylvain Gugger, Mariama Drame, Quentin Lhoest, and Alexander Rush. 2020 · 2020
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Adversarial attacks for tabular data: Application to fraud detection and imbalanced data
Francesco Cartella, Orlando Anunciação, Yuki Funabiki, Daisuke Yamaguchi, Toru Akishita, and Olivier Elshocht. 2021 · 2021
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Structure-grounded pretraining for text-to-SQL
Xiang Deng, Ahmed Hassan Awadallah, Christopher Meek, Oleksandr Polozov, Huan Sun, and Matthew Richardson. 2021 · 2021
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Few-nerd: A few-shot named entity recognition dataset
Ning Ding, Guangwei Xu, Yulin Chen, Xiaobin Wang, Xu Han, Pengjun Xie, Hai-Tao Zheng, and Zhiyuan Liu. 2021 · 2021
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Towards robustness of text-to-SQL models against synonym substitution
Yujian Gan, Xinyun Chen, Qiuping Huang, Matthew Purver, John R. Woodward, Jinxia Xie, and Pengsheng Huang. 2021 · 2021
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Simcse: Simple contrastive learning of sentence embeddings
Tianyu Gao, Xingcheng Yao, and Danqi Chen. 2021 · 2021
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Open domain question answering over tables via dense retrieval
Jonathan Herzig, Thomas Müller, Syrine Krichene, and Julian Martin Eisenschlos. 2021 · 2021
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On robustness of neural semantic parsers
Shuo Huang, Zhuang Li, Lizhen Qu, and Lei Pan. 2021 · 2021
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Awakening latent grounding from pretrained language models for semantic parsing
Qian Liu, Dejian Yang, Jiahui Zhang, Jiaqi Guo, Bin Zhou, and Jian-Guang Lou. 2021 · 2021
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DuoRAT: Towards simpler text-to-SQL models
Torsten Scholak, Raymond Li, Dzmitry Bahdanau, Harm de Vries, and Chris Pal. 2021 · 2021
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Adversarial examples for evaluating reading comprehension systems
Robin Jia and Percy Liang. 2017 · 2031
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