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Recent studies have revealed that \textit{Backdoor Attacks} can threaten the safety of natural language processing (NLP) models.
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.
Distilbert, a distilled version of bert: smaller, faster, cheaper and lighter
Victor Sanh, Lysandre Debut, Julien Chaumond, and Thomas Wolf. 2019 · 1910
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Label-consistent backdoor attacks
Alexander Turner, Dimitris Tsipras, and Aleksander Madry. 2019 · 1912
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A farewell to entropy: Statistical thermodynamics based on information: S
Arieh Ben-Naim. 2008 · 2008
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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 Y Ng, and Christopher Potts. 2013 · 2013
Earlier work this paper cites.
Character-level convolutional networks for text classification
Xiang Zhang, Junbo Zhao, and Yann LeCun. 2015 · 2015
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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.
Automated hate speech detection and the problem of offensive language
Thomas Davidson, Dana Warmsley, Michael Macy, and Ingmar Weber. 2017 · 2017
Earlier work this paper cites.
Trojaning attack on neural networks
Yingqi Liu, Shiqing Ma, Yousra Aafer, Wen-Chuan Lee, Juan Zhai, Weihang Wang, and Xiangyu Zhang. 2017 · 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 · 2017
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Adversarial example generation with syntactically controlled paraphrase networks
Mohit Iyyer, John Wieting, Kevin Gimpel, and Luke Zettlemoyer. 2018 · 2018
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What does bert look at? an analysis of bert’s attention
Kevin Clark, Urvashi Khandelwal, Omer Levy, and Christopher D Manning. 2019 · 2019
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A backdoor attack against lstm-based text classification systems
Jiazhu Dai, Chuanshuai Chen, and Yufeng Li. 2019 · 2019
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
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Are sixteen heads really better than one?
Paul Michel, Omer Levy, and Graham Neubig. 2019 · 2019
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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 · 2019
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Analyzing multi-head self-attention: Specialized heads do the heavy lifting, the rest can be pruned
Elena Voita, David Talbot, Fedor Moiseev, Rico Sennrich, and Ivan Titov. 2019 · 2019
Earlier work this paper cites.
Gradient shaping: Enhancing backdoor attack against reverse engineering
Rui Zhu, Di Tang, Siyuan Tang, Guanhong Tao, Shiqing Ma, Xiaofeng Wang, and Haixu Tang. 2023 · 2019
Earlier work this paper cites.
Live trojan attacks on deep neural networks
Robby Costales, Chengzhi Mao, Raphael Norwitz, Bryan Kim, and Junfeng Yang. 2020 · 2020
Cited alongside, same era.
Reformulating unsupervised style transfer as paraphrase generation
Kalpesh Krishna, John Wieting, and Mohit Iyyer. 2020 · 2020
Cited alongside, same era.
Weight poisoning attacks on pretrained models
Keita Kurita, Paul Michel, and Graham Neubig. 2020 · 2020
Cited alongside, same era.
A survey on neural trojans
Yuntao Liu, Ankit Mondal, Abhishek Chakraborty, Michael Zuzak, Nina Jacobsen, Daniel Xing, and Ankur Srivastava. 2020 · 2020
Cited alongside, same era.
Input-aware dynamic backdoor attack
Tuan Anh Nguyen and Anh Tran. 2020 · 2020
Cited alongside, same era.
Hidden trigger backdoor attacks
Aniruddha Saha, Akshayvarun Subramanya, and Hamed Pirsiavash. 2020 · 2020
Cited alongside, same era.
Backdoor attacks against deep learning systems in the physical world
Emily Wenger, Josephine Passananti, Arjun Nitin Bhagoji, Yuanshun Yao, Haitao Zheng, and Ben Y Zhao. 2021 · 2021
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Rap: Robustness-aware perturbations for defending against backdoor attacks on nlp models
Wenkai Yang, Yankai Lin, Peng Li, Jie Zhou, and Xu Sun. 2021b · 2021
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Trojaning language models for fun and profit
Xinyang Zhang, Zheng Zhang, Shouling Ji, and Ting Wang. 2021a · 2021
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Topological detection of trojaned neural networks
Songzhu Zheng, Yikai Zhang, Hubert Wagner, Mayank Goswami, and Chao Chen. 2021 · 2021
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A unified evaluation of textual backdoor learning: Frameworks and benchmarks
Ganqu Cui, Lifan Yuan, Bingxiang He, Yangyi Chen, Zhiyuan Liu, and Maosong Sun. 2022 · 2022
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Topogan: A topology-aware generative adversarial network
Fan Wang, Huidong Liu, Dimitris Samaras, and Chao Chen. 2020 · 2020
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. 2021 · 2021
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, Shangwei Guo, and Chun Fan. 2021 · 2021
Cited alongside, same era.
An overview of backdoor attacks against deep neural networks and possible defences
Wei Guo, Benedetta Tondi, and Mauro Barni. 2021 · 2021
Cited alongside, same era.
Self-attention attribution: Interpreting information interactions inside transformer
Yaru Hao, Li Dong, Furu Wei, and Ke Xu. 2021 · 2021
Cited alongside, same era.
On the distribution, sparsity, and inference-time quantization of attention values in transformers
Tianchu Ji, Shraddhan Jain, Michael Ferdman, Peter Milder, H Andrew Schwartz, and Niranjan Balasubramanian. 2021 · 2021
Cited alongside, same era.
A multimodal transformer: Fusing clinical notes with structured ehr data for interpretable in-hospital mortality prediction
Weimin Lyu, Xinyu Dong, Rachel Wong, Songzhu Zheng, Kayley Abell-Hart, Fusheng Wang, and Chao Chen. 2022a · 2022
Later among the works it cites.
A study of the attention abnormality in trojaned berts
Weimin Lyu, Songzhu Zheng, Tengfei Ma, and Chao Chen. 2022b · 2022
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Sleeper agent: Scalable hidden trigger backdoors for neural networks trained from scratch
Hossein Souri, Liam Fowl, Rama Chellappa, Micah Goldblum, and Tom Goldstein. 2022 · 2022
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Backdoor vulnerabilities in normally trained deep learning models
Guanhong Tao, Zhenting Wang, Siyuan Cheng, Shiqing Ma, Shengwei An, Yingqi Liu, Guangyu Shen, Zhuo Zhang, Yunshu Mao, and Xiangyu Zhang. 2022 · 2022
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A survey of neural trojan attacks and defenses in deep learning
Jie Wang, Ghulam Mubashar Hassan, and Naveed Akhtar. 2022 · 2022
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Narcissus: A practical clean-label backdoor attack with limited information
Yi Zeng, Minzhou Pan, Hoang Anh Just, Lingjuan Lyu, Meikang Qiu, and Ruoxi Jia. 2022 · 2022
Later among the works it cites.
Neurotoxin: Durable backdoors in federated learning
Zhengming Zhang, Ashwinee Panda, Linyue Song, Yaoqing Yang, Michael Mahoney, Prateek Mittal, Ramchandran Kannan, and Joseph Gonzalez. 2022 · 2022
Later among the works it cites.
How to backdoor diffusion models?
Sheng-Yen Chou, Pin-Yu Chen, and Tsung-Yi Ho · 2023
Closest in time.
Sok: Certified robustness for deep neural networks
Linyi Li, Tao Xie, and Bo Li. 2022a · 2023
Closest in time.
Backdoor cleansing with unlabeled data
Lu Pang, Tao Sun, Haibin Ling, and Chao Chen. 2023 · 2023
Closest in time.
Unicorn: A unified backdoor trigger inversion framework
Zhenting Wang, Kai Mei, Juan Zhai, and Shiqing Ma. 2023 · 2023
Closest in time.
Be careful about poisoned word embeddings: Exploring the vulnerability of the embedding layers in nlp models
Wenkai Yang, Lei Li, Zhiyuan Zhang, Xuancheng Ren, Xu Sun, and Bin He. 2021a · 2058
Closest in time.