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Adversarial attacks alter NLP model predictions by perturbing test-time inputs.
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
Earlier work this paper cites.
Jason Baumgartner, Savvas Zannettou, Brian Keegan, Megan Squire, and Jeremy Blackburn. 2020 · 2001
Earlier work this paper cites.
Recipes for building an open-domain chatbot
Stephen Roller, Emily Dinan, Naman Goyal, Da Ju, Mary Williamson, Yinhan Liu, Jing Xu, Myle Ott, Kurt Shuster, Eric M Smith, et al. 2020 · 2004
Earlier work this paper cites.
Subpopulation data poisoning attacks
Matthew Jagielski, Giorgio Severi, Niklas Pousette Harger, and Alina Oprea. 2020 · 2006
Earlier work this paper cites.
Exploiting machine learning to subvert your spam filter
Blaine Nelson, Marco Barreno, Fuching Jack Chi, Anthony D Joseph, Benjamin IP Rubinstein, Udam Saini, Charles A Sutton, J Doug Tygar, and Kai Xia. 2008 · 2008
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Poisoning attacks against support vector machines
Battista Biggio, Blaine Nelson, and Pavel Laskov. 2012 · 2012
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Recursive deep models for semantic compositionality over a sentiment treebank
Richard Socher, Alex Perelygin, Jean Wu, Jason Chuang, Christopher D Manning, Andrew Ng, and Christopher Potts. 2013 · 2013
Earlier work this paper cites.
Report on the 11th IWSLT evaluation campaign
Mauro Cettolo, Jan Niehues, Sebastian Stuker, Luisa Bentivogli, and Marcello Federico. 2014 · 2014
Earlier work this paper cites.
Learning from tay’s introduction
Peter Lee. 2016 · 2016
Earlier work this paper cites.
Targeted backdoor attacks on deep learning systems using data poisoning
Xinyun Chen, Chang Liu, Bo Li, Kimberly Lu, and Dawn Song. 2017 · 2017
Earlier work this paper cites.
Model-agnostic meta-learning for fast adaptation of deep networks
Chelsea Finn, Pieter Abbeel, and Sergey Levine. 2017 · 2017
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Adversarial examples for evaluating reading comprehension systems
Robin Jia and Percy Liang. 2017 · 2017
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Understanding black-box predictions via influence functions
Pang Wei Koh and Percy Liang. 2017 · 2017
Earlier work this paper cites.
Pointer sentinel mixture models
Stephen Merity, Caiming Xiong, James Bradbury, and Richard Socher. 2017 · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Cited alongside, same era.
Data statements for natural language processing: Toward mitigating system bias and enabling better science
Emily M Bender and Batya Friedman. 2018 · 2018
Cited alongside, same era.
Attacks against machine learning—an overview
Elie Bursztein. 2018 · 2018
Cited alongside, same era.
HotFlip: White-box adversarial examples for text classification
Javid Ebrahimi, Anyi Rao, Daniel Lowd, and Dejing Dou. 2018 · 2018
Cited alongside, same era.
Hierarchical neural story generation
Angela Fan, Mike Lewis, and Yann Dauphin. 2018 · 2018
Cited alongside, same era.
Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna Wallach, Hal Daumeé III, and Kate Crawford. 2018 · 2018
fairseq: A fast, extensible toolkit for sequence modeling
Myle Ott, Sergey Edunov, Alexei Baevski, Angela Fan, Sam Gross, Nathan Ng, David Grangier, and Michael Auli. 2019 · 2019
Later among the works it cites.
Investigating robustness and interpretability of link prediction via adversarial modifications
Pouya Pezeshkpour, Yifan Tian, and Sameer Singh. 2019 · 2019
Later among the works it cites.
Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever. 2019 · 2019
Later among the works it cites.
The risk of racial bias in hate speech detection
Maarten Sap, Dallas Card, Saadia Gabriel, Yejin Choi, and Noah A Smith. 2019 · 2019
Later among the works it cites.
Universal adversarial triggers for attacking and analyzing NLP
Eric Wallace, Shi Feng, Nikhil Kandpal, Matt Gardner, and Sameer Singh. 2019 · 2019
Later among the works it cites.
Poison attacks against text datasets with conditional adversarially regularized autoencoder
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Cited alongside, same era.
Annotation artifacts in natural language inference data
Suchin Gururangan, Swabha Swayamdipta, Omer Levy, Roy Schwartz, Samuel R. Bowman, and Noah A. Smith. 2018 · 2018
Cited alongside, same era.
Poison frogs! targeted clean-label poisoning attacks on neural networks
Ali Shafahi, W Ronny Huang, Mahyar Najibi, Octavian Suciu, Christoph Studer, Tudor Dumitras, and Tom Goldstein. 2018 · 2018
Cited alongside, same era.
Ensemble adversarial training: Attacks and defenses
Florian Tramèr, Alexey Kurakin, Nicolas Papernot, Ian Goodfellow, Dan Boneh, and Patrick McDaniel. 2018 · 2018
Cited alongside, same era.
Clean-label backdoor attacks
Alexander Turner, Dimitris Tsipras, and Aleksander Madry. 2018 · 2018
Cited alongside, same era.
Tongzhou Wang, Jun-Yan Zhu, Antonio Torralba, and Alexei A Efros. 2018 · 2018
Cited alongside, same era.
Don’t take the easy way out: Ensemble based methods for avoiding known dataset biases
Christopher Clark, Mark Yatskar, and Luke Zettlemoyer. 2019 · 2019
Cited alongside, same era.
Alvin Chan, Yi Tay, Yew-Soon Ong, and Aston Zhang. 2020 · 2020
Closest in time.
Evaluating models’ local decision boundaries via contrast sets
Matt Gardner, Yoav Artzi, Victoria Basmov, Jonathan Berant, Ben Bogin, Sihao Chen, Pradeep Dasigi, Dheeru Dua, Yanai Elazar, Ananth Gottumukkala, Nitish Gupta, Hannaneh Hajishirzi, Gabriel Ilharco, Daniel Khashabi, Kevin Lin, Jiangming Liu, Nelson F. Liu, Phoebe Mulcaire, Qiang Ning, Sameer Singh, Noah A. Smith, Sanjay Subramanian, Reut Tsarfaty, Eric Wallace, Ally Zhang, and Ben Zhou. 2020 · 2020
Closest in time.
MetaPoison: practical general-purpose clean-label data poisoning
W Ronny Huang, Jonas Geiping, Liam Fowl, Gavin Taylor, and Tom Goldstein. 2020 · 2020
Closest in time.
Weight poisoning attacks on pretrained models
Keita Kurita, Paul Michel, and Graham Neubig. 2020 · 2020
Closest in time.
Hidden trigger backdoor attacks
Aniruddha Saha, Akshayvarun Subramanya, and Hamed Pirsiavash. 2020 · 2020
Closest in time.
Humpty Dumpty: Controlling word meanings via corpus poisoning
Roei Schuster, Tal Schuster, Yoav Meri, and Vitaly Shmatikov. 2020 · 2020
Closest in time.
You autocomplete me: Poisoning vulnerabilities in neural code completion
Roei Schuster, Congzheng Song, Eran Tromer, and Vitaly Shmatikov. 2021 · 2021
Closest in time.
Wenkai Yang, Lei Li, Zhiyuan Zhang, Xuancheng Ren, Xu Sun, and Bin He. 2021 · 2021
Closest in time.