Fetching the paper…
Reading the bibliography…
Deep neural networks (DNNs) have long been recognized as vulnerable to backdoor attacks.
Nltk: The natural language toolkit
Edward Loper and Steven Bird · 2002
Earlier work this paper cites.
Ranking a stream of news
Gianna M Del Corso, Antonio Gulli, and Francesco Romani · 2005
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
Earlier work this paper cites.
Recursive deep models for semantic compositionality over a sentiment treebank
Richard Socher, Alex Perelygin, Jean Wu, Jason Chuang, Christopher D Manning, Andrew Y Ng, and Christopher Potts · 2013
Earlier work this paper cites.
Principal component analysis: a review and recent developments
Ian T Jolliffe and Jorge Cadima · 2016
Earlier work this paper cites.
Badnets: Identifying vulnerabilities in the machine learning model supply chain
Tianyu Gu, Brendan Dolan-Gavitt, and Siddharth Garg · 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.
Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
Earlier work this paper cites.
CARER: Contextualized affect representations for emotion recognition
Elvis Saravia, Hsien-Chi Toby Liu, Yen-Hao Huang, Junlin Wu, and Yi-Shin Chen · 2018
Earlier work this paper cites.
Deep learning for computer vision: A brief review
Athanasios Voulodimos, Nikolaos Doulamis, Anastasios Doulamis, and Eftychios Protopapadakis · 2018
Earlier work this paper cites.
A backdoor attack against lstm-based text classification systems
Jiazhu Dai, Chuanshuai Chen, and Yufeng Li · 2019
Earlier work this paper cites.
Distilbert, a distilled version of bert: smaller, faster, cheaper and lighter
Victor Sanh, Lysandre Debut, Julien Chaumond, and Thomas Wolf · 2019
Cited alongside, same era.
Weight poisoning attacks on pre-trained models
Keita Kurita, Paul Michel, and Graham Neubig · 2020
Cited alongside, same era.
A survey of the usages of deep learning for natural language processing
Daniel W Otter, Julian R Medina, and Jugal K Kalita · 2020
Cited alongside, same era.
Onion: A simple and effective defense against textual backdoor attacks
Fanchao Qi, Yangyi Chen, Mukai Li, Yuan Yao, Zhiyuan Liu, and Maosong Sun · 2020
Cited alongside, same era.
Badnl: Backdoor attacks against nlp models with semantic-preserving improvements
Xiaoyi Chen, Ahmed Salem, Dingfan Chen, Michael Backes, Shiqing Ma, Qingni Shen, Zhonghai Wu, and Yang Zhang · 2021
Membership inference attacks by exploiting loss trajectory
Yiyong Liu, Zhengyu Zhao, Michael Backes, and Yang Zhang · 2022
Later among the works it cites.
Hidden trigger backdoor attack on { \{ NLP } \} models via linguistic style manipulation
Xudong Pan, Mi Zhang, Beina Sheng, Jiaming Zhu, and Min Yang · 2022
Later among the works it cites.
Towards data-free model stealing in a hard label setting
Sunandini Sanyal, Sravanti Addepalli, and R. Venkatesh Babu · 2022
Later among the works it cites.
Architectural backdoors in neural networks
Mikel Bober-Irizar, Ilia Shumailov, Yiren Zhao, Robert Mullins, and Nicolas Papernot · 2023
Later among the works it cites.
Composite backdoor attacks against large language models
Hai Huang, Zhengyu Zhao, Michael Backes, Yun Shen, and Yang Zhang · 2023
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Triggerless backdoor attack for nlp tasks with clean labels
Leilei Gan, Jiwei Li, Tianwei Zhang, Xiaoya Li, Yuxian Meng, Fei Wu, Yi Yang, Shangwei Guo, and Chun Fan · 2021
Cited alongside, same era.
Hidden backdoors in human-centric language models
Shaofeng Li, Hui Liu, Tian Dong, Benjamin Zi Hao Zhao, Minhui Xue, Haojin Zhu, and Jialiang Lu · 2021
Cited alongside, same era.
Bddr: An effective defense against textual backdoor attacks
Kun Shao, Junan Yang, Yang Ai, Hui Liu, and Yu Zhang · 2021
Cited alongside, same era.
Wenkai Yang, Lei Li, Zhiyuan Zhang, Xuancheng Ren, Xu Sun, and Bin He · 2021
Cited alongside, same era.
Rap: Robustness-aware perturbations for defending against backdoor attacks on nlp models
Wenkai Yang, Yankai Lin, Peng Li, Jie Zhou, and Xu Sun · 2021
Cited alongside, same era.
Textual backdoor attacks can be more harmful via two simple tricks
Yangyi Chen, Fanchao Qi, Hongcheng Gao, Zhiyuan Liu, and Maosong Sun · 2022
Cited alongside, same era.
{ \{ T-Miner } \} : A generative approach to defend against trojan attacks on { \{ DNN-based } \} text classification
Ahmadreza Azizi, Ibrahim Asadullah Tahmid, Asim Waheed, Neal Mangaokar, Jiameng Pu, Mobin Javed, Chandan K Reddy, and Bimal Viswanath
Cited in the paper.
Yujin Huang, Terry Yue Zhuo, Qiongkai Xu, Han Hu, Xingliang Yuan, and Chunyang Chen · 2023
Later among the works it cites.
K-means clustering algorithms: A comprehensive review, variants analysis, and advances in the era of big data
Abiodun M Ikotun, Absalom E Ezugwu, Laith Abualigah, Belal Abuhaija, and Jia Heming · 2023
Later among the works it cites.
Punctuation matters! stealthy backdoor attack for language models
Xuan Sheng, Zhicheng Li, Zhaoyang Han, Xiangmao Chang, and Piji Li · 2023
Later among the works it cites.
Emtract: Extracting emotions from social media
Domonkos F Vamossy and Rolf Skog · 2023
Later among the works it cites.
Bite: Textual backdoor attacks with iterative trigger injection
Jun Yan, Vansh Gupta, and Xiang Ren · 2023
Later among the works it cites.
Improving probability-based prompt selection through unified evaluation and analysis
Sohee Yang, Jonghyeon Kim, Joel Jang, Seonghyeon Ye, Hyunji Lee, and Minjoon Seo · 2023
Later among the works it cites.