Fetching the paper…
Reading the bibliography…
Existing textual adversarial attacks usually utilize the gradient or prediction confidence to generate adversarial examples, making it hard to be deployed in real-world applications.
Genetic set recombination
Nicholas J Radcliffe. 1993 · 1993
Earlier work this paper cites.
Genetic algorithms for combinatorial optimization: the assemble line balancing problem
Edward J Anderson and Michael C Ferris. 1994 · 1994
Earlier work this paper cites.
Particle swarm optimization
James Kennedy and Russell Eberhart. 1995 · 1995
Earlier work this paper cites.
Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber. 1997 · 1997
Earlier work this paper cites.
Hybrid evolutionary algorithms for graph coloring
Philippe Galinier and Jin-Kao Hao. 1999 · 1999
Earlier work this paper cites.
Local search in combinatorial optimization
Emile Aarts, Emile HL Aarts, and Jan Karel Lenstra. 2003 · 2003
Earlier work this paper cites.
Seeing stars: Exploiting class relationships for sentiment categorization with respect to rating scales
Bo Pang and Lillian Lee. 2005 · 2005
Earlier work this paper cites.
Textdecepter: Hard label black box attack on text classifiers
Sachin Saxena. 2020 · 2008
Earlier work this paper cites.
Learning to attack: Towards textual adversarial attacking in real-world situations
Yuan Zang, Bairu Hou, Fanchao Qi, Zhiyuan Liu, Xiaojun Meng, and Maosong Sun. 2020a · 2009
Earlier work this paper cites.
Learning word vectors for sentiment analysis
Andrew L. Maas, Raymond E. Daly, Peter T. Pham, Dan Huang, Andrew Y. Ng, and Christopher Potts. 2011 · 2011
Earlier work this paper cites.
Convolutional neural networks for sentence classification
Yoon Kim. 2014 · 2014
Earlier work this paper cites.
Intriguing properties of neural networks
Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian J. Goodfellow, and Rob Fergus. 2014 · 2014
Earlier work this paper cites.
A large annotated corpus for learning natural language inference
Samuel R. Bowman, Gabor Angeli, Christopher Potts, and Christopher D. Manning. 2015 · 2015
Cited alongside, same era.
Explaining and harnessing adversarial examples
Ian J. Goodfellow, Jonathon Shlens, and Christian Szegedy. 2015 · 2015
Cited alongside, same era.
Character-level convolutional networks for text classification
Xiang Zhang, Junbo Jake Zhao, and Yann LeCun. 2015 · 2015
Cited alongside, same era.
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
Cited alongside, same era.
Crafting adversarial input sequences for recurrent neural networks
Nicolas Papernot, Patrick McDaniel, Ananthram Swami, and Richard Harang. 2016 · 2016
Cited alongside, same era.
BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Later among the works it cites.
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.
Generating natural language adversarial examples through probability weighted word saliency
Shuhuai Ren, Yihe Deng, Kun He, and Wanxiang Che. 2019 · 2019
Later among the works it cites.
Generating fluent adversarial examples for natural languages
Huangzhao Zhang, Hao Zhou, Ning Miao, and Lei Li. 2019 · 2019
Later among the works it cites.
BAE: BERT-based adversarial examples for text classification
Siddhant Garg and Goutham Ramakrishnan. 2020 · 2020
Later among the works it cites.
Is BERT really robust? A strong baseline for natural language attack on text classification and entailment
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Generating natural language adversarial examples
Moustafa Alzantot, Yash Sharma, Ahmed Elgohary, Bo-Jhang Ho, Mani Srivastava, and Kai-Wei Chang. 2018 · 2018
Cited alongside, same era.
Daniel Cer, Yinfei Yang, Sheng-yi Kong, Nan Hua, Nicole Limtiaco, Rhomni St John, Noah Constant, Mario Guajardo-Céspedes, Steve Yuan, Chris Tar, et al. 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.
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.
Deep text classification can be fooled
Bin Liang, Hongcheng Li, Miaoqiang Su, Pan Bian, Xirong Li, and Wenchang Shi. 2018 · 2018
Cited alongside, same era.
Towards deep learning models resistant to adversarial attacks
Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, and Adrian Vladu. 2018 · 2018
Cited alongside, same era.
A broad-coverage challenge corpus for sentence understanding through inference
Adina Williams, Nikita Nangia, and Samuel Bowman. 2018 · 2018
Cited alongside, same era.
Di Jin, Zhijing Jin, Joey Tianyi Zhou, and Peter Szolovits. 2020 · 2020
Later among the works it cites.
A geometry-inspired attack for generating natural language adversarial examples
Zhao Meng and Roger Wattenhofer. 2020 · 2020
Later among the works it cites.
Greedy attack and gumbel attack: Generating adversarial examples for discrete data
Puyudi Yang, Jianbo Chen, Cho-Jui Hsieh, Jane-Ling Wang, and Michael I Jordan. 2020 · 2020
Later among the works it cites.
Generating natural language attacks in a hard label black box setting
Rishabh Maheshwary, Saket Maheshwary, and Vikram Pudi. 2021 · 2021
Later among the works it cites.
Randomized substitution and vote for textual adversarial example detection
Xiaosen Wang, Yifeng Xiong, and Kun He. 2022 · 2022
Closest in time.
Robust textual embedding against word-level adversarial attacks
Yichen Yang, Xiaosen Wang, and Kun He. 2022 · 2022
Closest in time.
Texthoaxer: Budgeted hard-label adversarial attacks on text
Muchao Ye, Chenglin Miao, Ting Wang, and Fenglong Ma. 2022 · 2022
Closest in time.