Fetching the paper…
Reading the bibliography…
While there has been substantial research using adversarial attacks to analyze NLP models, each attack is implemented in its own code repository.
EDA: easy data augmentation techniques for boosting performance on text classification tasks
Jason W. Wei and Kai Zou. 2019 · 1901
Earlier work this paper cites.
On evaluation of adversarial perturbations for sequence-to-sequence models
Paul Michel, Xian Li, Graham Neubig, and Juan Miguel Pino. 2019 · 1903
Earlier work this paper cites.
Is bert really robust? natural language attack on text classification and entailment
Di Jin, Zhijing Jin, Joey Tianyi Zhou, and Peter Szolovits. 2019 · 1907
Earlier work this paper cites.
Allennlp interpret: A framework for explaining predictions of nlp models
Eric Wallace, Jens Tuyls, Junlin Wang, Sanjay Subramanian, Matthew Gardner, and Sameer Singh. 2019 · 1909
Earlier work this paper cites.
Particle swarm optimization
James Kennedy and Russell Eberhart. 1995 · 1948
Earlier work this paper cites.
Introduction to wordnet: An on-line lexical database
George Armitage Miller, Richard Beckwith, Christiane Fellbaum, Derek Gross, and Katherine J. Miller. 1990 · 1990
Earlier work this paper cites.
Bleu: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2001 · 2001
Earlier work this paper cites.
A rule-based style and grammar checker
Daniel Naber et al. 2003 · 2003
Earlier work this paper cites.
Hownet and the computation of meaning
Zhendong Dong, Qiang Dong, and Changling Hao. 2006 · 2006
Earlier work this paper cites.
Meteor, m-bleu and m-ter: Evaluation metrics for high-correlation with human rankings of machine translation output
Abhaya Agarwal and Alon Lavie. 2008 · 2008
Earlier work this paper cites.
Ryan Kiros, Yukun Zhu, Ruslan Salakhutdinov, Richard S. Zemel, Raquel Urtasun, Antonio Torralba, and Sanja Fidler. 2015 · 2015
Earlier work this paper cites.
chrf: character n-gram f-score for automatic mt evaluation
Maja Popovic. 2015 · 2015
Earlier work this paper cites.
Exploring the limits of language modeling
Rafal Józefowicz, Oriol Vinyals, Mike Schuster, Noam Shazeer, and Yonghui Wu. 2016 · 2016
Earlier work this paper cites.
Counter-fitting word vectors to linguistic constraints
Nikola Mrkšić, Diarmuid O Séaghdha, Blaise Thomson, Milica Gašić, Lina Rojas-Barahona, Pei-Hao Su, David Vandyke, Tsung-Hsien Wen, and Steve Young. 2016 · 2016
Cited alongside, same era.
Supervised learning of universal sentence representations from natural language inference data
Alexis Conneau, Douwe Kiela, Holger Schwenk, Loïc Barrault, and Antoine Bordes. 2017 · 2017
Cited alongside, same era.
Hotflip: White-box adversarial examples for text classification
Javid Ebrahimi, Anyi Rao, Daniel Lowd, and Dejing Dou. 2017 · 2017
Cited alongside, same era.
Generating natural language adversarial examples
Moustafa Alzantot, Yash Sharma, Ahmed Elgohary, Bo-Jhang Ho, Mani B. Srivastava, and Kai-Wei Chang. 2018 · 2018
Cited alongside, same era.
Textbugger: Generating adversarial text against real-world applications
Jinfeng Li, Shouling Ji, Tianyu Du, Bo Li, and Ting Wang. 2019 · 2019
Later among the works it cites.
Combating adversarial misspellings with robust word recognition
Danish Pruthi, Bhuwan Dhingra, and Zachary C. Lipton. 2019 · 2019
Later among the works it cites.
Language models are unsupervised multitask learners
Alec Radford, Jeff Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever. 2019 · 2019
Later among the works it cites.
Sentence-bert: Sentence embeddings using siamese bert-networks
Nils Reimers and Iryna Gurevych. 2019 · 2019
Later among the works it cites.
Generating natural language adversarial examples through probability weighted word saliency
Shuhuai Ren, Yihe Deng, Kun He, and Wanxiang Che. 2019 · 2019
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Daniel Matthew Cer, Yinfei Yang, Sheng yi Kong, Nan Hua, Nicole Limtiaco, Rhomni St. John, Noah Constant, Mario Guajardo-Cespedes, Steve Yuan, Chris Tar, Yun-Hsuan Sung, Brian Strope, and Ray Kurzweil. 2018 · 2018
Cited alongside, same era.
Seq2sick: Evaluating the robustness of sequence-to-sequence models with adversarial examples
Minhao Cheng, Jinfeng Yi, Pin-Yu Chen, Huan Zhang, and Cho-Jui Hsieh. 2018 · 2018
Cited alongside, same era.
Pathologies of neural models make interpretations difficult
Shi Feng, Eric Wallace, Alvin Grissom II, Mohit Iyyer, Pedro Rodriguez, and Jordan Boyd-Graber. 2018 · 2018
Cited alongside, same era.
Black-box generation of adversarial text sequences to evade deep learning classifiers
Ji Gao, Jack Lanchantin, Mary Lou Soffa, and Yanjun Qi. 2018 · 2018
Cited alongside, same era.
Learning to write with cooperative discriminators
Ari Holtzman, Jan Buys, Maxwell Forbes, Antoine Bosselut, David Golub, and Yejin Choi. 2018 · 2018
Cited alongside, same era.
Adversarial examples for natural language classification problems
Volodymyr Kuleshov, Shantanu Thakoor, Tingfung Lau, and Stefano Ermon. 2018 · 2018
Cited alongside, same era.
Evading classifiers in discrete domains with provable optimality guarantees
Bogdan Kulynych, Jamie Hayes, Nikita Samarin, and Carmela Troncoso. 2018 · 2018
Cited alongside, same era.
Technical report on the cleverhans v2.1.0 adversarial examples library
Nicolas Papernot, Fartash Faghri, Nicholas Carlini, Ian Goodfellow, Reuben Feinman, Alexey Kurakin, Cihang Xie, Yash Sharma, Tom Brown, Aurko Roy, Alexander Matyasko, Vahid Behzadan, Karen Hambardzumyan, Zhishuai Zhang, Yi-Lin Juang, Zhi Li, Ryan Sheatsley, Abhibhav Garg, Jonathan Uesato, Willi Gierke, Yinpeng Dong, David Berthelot, Paul Hendricks, Jonas Rauber, and Rujun Long. 2018 · 2018
Cited alongside, same era.
Later among the works it cites.
Natural language adversarial attacks and defenses in word level
Xiaosen Wang, Hao Jin, and Kun He. 2019 · 2019
Later among the works it cites.
Transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, R’emi Louf, Morgan Funtowicz, and Jamie Brew. 2019 · 2019
Later among the works it cites.
Bae: Bert-based adversarial examples for text classification
Siddhant Garg and Goutham Ramakrishnan. 2020 · 2020
Closest in time.
Bert-attack: Adversarial attack against bert using bert
Linyang Li, Ruotian Ma, Qipeng Guo, Xiangyang Xue, and Xipeng Qiu. 2020 · 2020
Closest in time.
It’s morphin’ time! Combating linguistic discrimination with inflectional perturbations
Samson Tan, Shafiq Joty, Min-Yen Kan, and Richard Socher. 2020 · 2020
Closest in time.
Word-level textual adversarial attacking as combinatorial optimization
Yuan Zang, Fanchao Qi, Chenghao Yang, Zhiyuan Liu, Meng Zhang, Qun Liu, and Maosong Sun. 2020 · 2020
Closest in time.
Bertscore: Evaluating text generation with bert
Tianyi Zhang*, Varsha Kishore*, Felix Wu*, Kilian Q. Weinberger, and Yoav Artzi. 2020 · 2020
Closest in time.
Adversarial examples for evaluating reading comprehension systems
Robin Jia and Percy Liang. 2017 · 2031
Closest in time.