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Deep neural networks have been shown to be vulnerable to small perturbations of their inputs, known as adversarial attacks.
A rule-based style and grammar checker
Daniel Naber et al · 2003
Earlier work this paper cites.
Parallel data, tools and interfaces in opus
Jörg Tiedemann · 2012
Earlier work this paper cites.
Continuous measurement scales in human evaluation of machine translation
Yvette Graham, Timothy Baldwin, Alistair Moffat, and Justin Zobel · 2013
Earlier work this paper cites.
Findings of the 2014 workshop on statistical machine translation
Ondřej Bojar, Christian Buck, Christian Federmann, Barry Haddow, Philipp Koehn, Johannes Leveling, Christof Monz, Pavel Pecina, Matt Post, Herve Saint-Amand, et al · 2014
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
Earlier work this paper cites.
Intriguing properties of neural networks
Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian Goodfellow, and Rob Fergus · 2014
Earlier work this paper cites.
Neural machine translation by jointly learning to align and translate
Dzmitry Bahdanau, Kyung Hyun Cho, and Yoshua Bengio · 2015
Earlier work this paper cites.
chrf: character n-gram f-score for automatic mt evaluation
Maja Popović · 2015
Earlier work this paper cites.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Earlier work this paper cites.
Deepfool: a simple and accurate method to fool deep neural networks
Seyed-Mohsen Moosavi-Dezfooli, Alhussein Fawzi, and Pascal Frossard · 2016
Earlier work this paper cites.
Semeval-2017 task 1: Semantic textual similarity multilingual and crosslingual focused evaluation
Daniel Cer, Mona Diab, Eneko Agirre, Iñigo Lopez-Gazpio, and Lucia Specia · 2017
Earlier work this paper cites.
Can machine translation systems be evaluated by the crowd alone
Yvette Graham, Timothy Baldwin, Alistair Moffat, and Justin Zobel · 2017
Earlier work this paper cites.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
Earlier work this paper cites.
Generating natural language adversarial examples
Moustafa Alzantot, Yash Sharma, Ahmed Elgohary, Bo-Jhang Ho, Mani Srivastava, and Kai-Wei Chang · 2018
Earlier work this paper cites.
Synthetic and natural noise both break neural machine translation
Yonatan Belinkov and Yonatan Bisk · 2018
Earlier work this paper cites.
Towards robust neural machine translation
Yong Cheng, Zhaopeng Tu, Fandong Meng, Junjie Zhai, and Yang Liu · 2018
Earlier work this paper cites.
Marian: Fast neural machine translation in C++
Marcin Junczys-Dowmunt, Roman Grundkiewicz, Tomasz Dwojak, Hieu Hoang, Kenneth Heafield, Tom Neckermann, Frank Seide, Ulrich Germann, Alham Fikri Aji, Nikolay Bogoychev, André F. T. Martins, and Alexandra Birch · 2018
Earlier work this paper cites.
Results of the wmt18 metrics shared task: Both characters and embeddings achieve good performance
Qingsong Ma, Ondřej Bojar, and Yvette Graham · 2018
Earlier work this paper cites.
Towards deep learning models resistant to adversarial attacks
Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, and Adrian Vladu · 2018
Earlier work this paper cites.
Exploring the robustness of nmt systems to nonsensical inputs
Akshay Chaturvedi, Abijith KP, and Utpal Garain · 2019
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Robust neural machine translation with doubly adversarial inputs
Yong Cheng, Lu Jiang, and Wolfgang Macherey · 2019
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On evaluation of adversarial perturbations for sequence-to-sequence models
Paul Michel, Xian Li, Graham Neubig, and Juan Pino · 2019
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Facebook fair’s wmt19 news translation task submission
Nathan Ng, Kyra Yee, Alexei Baevski, Myle Ott, Michael Auli, and Sergey Edunov · 2019
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Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, et al · 2019
Cited alongside, same era.
Multilingual universal sentence encoder for semantic retrieval
Yinfei Yang, Daniel Cer, Amin Ahmad, Mandy Guo, Jax Law, Noah Constant, Gustavo Hernandez Abrego, Steve Yuan, Chris Tar, Yun-Hsuan Sung, et al · 2020
Later among the works it cites.
Word-level textual adversarial attacking as combinatorial optimization
Yuan Zang, Fanchao Qi, Chenghao Yang, Zhiyuan Liu, Meng Zhang, Qun Liu, and Maosong Sun · 2020
Later among the works it cites.
Improving massively multilingual neural machine translation and zero-shot translation
Biao Zhang, Philip Williams, Ivan Titov, and Rico Sennrich · 2020
Later among the works it cites.
Seeds of seed: Nmt-stroke: Diverting neural machine translation through hardware-based faults
Kunbei Cai, Md Hafizul Islam Chowdhuryy, Zhenkai Zhang, and Fan Yao · 2021
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Ignorance is bliss: Exploring defenses against invariance-based attacks on neural machine translation systems
Akshay Chaturvedi, Abhisek Chakrabarty, Masao Utiyama, Eiichiro Sumita, and Utpal Garain · 2021
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al · 2019
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Generating natural language adversarial examples through probability weighted word saliency
Shuhuai Ren, Yihe Deng, Kun He, and Wanxiang Che · 2019
Cited alongside, same era.
What do you learn from context? probing for sentence structure in contextualized word representations
Ian Tenney, Patrick Xia, Berlin Chen, Alex Wang, Adam Poliak, R Thomas McCoy, Najoung Kim, Benjamin Van Durme, Samuel R Bowman, Dipanjan Das, et al · 2019
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Bertscore: Evaluating text generation with bert
Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q Weinberger, and Yoav Artzi · 2019
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Detecting word sense disambiguation biases in machine translation for model-agnostic adversarial attacks
Denis Emelin, Ivan Titov, and Rico Sennrich · 2020
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Is bert really robust? a strong baseline for natural language attack on text classification and entailment
Di Jin, Zhijing Jin, Joey Tianyi Zhou, and Peter Szolovits · 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
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Results of the wmt21 metrics shared task: Evaluating metrics with expert-based human evaluations on ted and news domain
Markus Freitag, Ricardo Rei, Nitika Mathur, Chi-kiu Lo, Craig Stewart, George Foster, Alon Lavie, and Ondřej Bojar · 2021
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Gradient-based adversarial attacks against text transformers
Chuan Guo, Alexandre Sablayrolles, Hervé Jégou, and Douwe Kiela · 2021
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Datasets: A community library for natural language processing
Quentin Lhoest, Albert Villanova del Moral, Yacine Jernite, Abhishek Thakur, Patrick von Platen, Suraj Patil, Julien Chaumond, Mariama Drame, Julien Plu, Lewis Tunstall, Joe Davison, Mario Šaško, Gunjan Chhablani, Bhavitvya Malik, Simon Brandeis, Teven Le Scao, Victor Sanh, Canwen Xu, Nicolas Patry, Angelina McMillan-Major, Philipp Schmid, Sylvain Gugger, Clément Delangue, Théo Matussière, Lysandre Debut, Stas Bekman, Pierric Cistac, Thibault Goehringer, Victor Mustar, François Lagunas, Alexander Rush, and Thomas Wolf · 2021
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Optimism in the face of adversity: Understanding and improving deep learning through adversarial robustness
Guillermo Ortiz-Jiménez, Apostolos Modas, Seyed-Mohsen Moosavi-Dezfooli, and Pascal Frossard · 2021
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Better neural machine translation by extracting linguistic information from bert
Hassan S Shavarani and Anoop Sarkar · 2021
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Doubly-trained adversarial data augmentation for neural machine translation
Weiting Tan, Shuoyang Ding, Huda Khayrallah, and Philipp Koehn · 2021
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Understanding the societal impacts of machine translation: a critical review of the literature on medical and legal use cases
Lucas Nunes Vieira, Minako O’Hagan, and Carol O’Sullivan · 2021
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Putting words into the system’s mouth: A targeted attack on neural machine translation using monolingual data poisoning
Jun Wang, Chang Xu, Francisco Guzmán, Ahmed El-Kishky, Yuqing Tang, Benjamin Rubinstein, and Trevor Cohn · 2021
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A targeted attack on black-box neural machine translation with parallel data poisoning
Chang Xu, Jun Wang, Yuqing Tang, Francisco Guzmán, Benjamin IP Rubinstein, and Trevor Cohn · 2021
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A2r2: Robust unsupervised neural machine translation with adversarial attack and regularization on representations
Heng Yu, Haoran Luo, Yuqi Yi, and Fan Cheng · 2021
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Crafting adversarial examples for neural machine translation
Xinze Zhang, Junzhe Zhang, Zhenhua Chen, and Kun He · 2021
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Block-sparse adversarial attack to fool transformer-based text classifiers
Sahar Sadrizadeh, Ljiljana Dolamic, and Pascal Frossard · 2022
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Semattack: Natural textual attacks via different semantic spaces
Boxin Wang, Chejian Xu, Xiangyu Liu, Yu Cheng, and Bo Li · 2022
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