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Backdoors implanted in pre-trained language models (PLMs) can be transferred to various downstream tasks, which exposes a severe security threat.
Universal adversarial triggers for attacking and analyzing nlp
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Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Ves Stoyanov, and Luke Zettlemoyer. 2019 · 1910
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A memory-based approach to anti-spam filtering for mailing lists
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Introduction to the conll-2003 shared task: Language-independent named entity recognition
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Weight poisoning attacks on pre-trained models
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Learning word vectors for sentiment analysis
Andrew Maas, Raymond E Daly, Peter T Pham, Dan Huang, Andrew Y Ng, and Christopher Potts. 2011 · 2011
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Onion: A simple and effective defense against textual backdoor attacks
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Richard Socher, Alex Perelygin, Jean Wu, Jason Chuang, Christopher D Manning, Andrew Y Ng, and Christopher Potts. 2013 · 2013
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Dbpedia–a large-scale, multilingual knowledge base extracted from wikipedia
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Character-level convolutional networks for text classification
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Hate speech dataset from a white supremacy forum
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018 · 2018
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Badpre: Task-agnostic backdoor attacks to pre-trained nlp foundation models
Kangjie Chen, Yuxian Meng, Xiaofei Sun, Shangwei Guo, Tianwei Zhang, Jiwei Li, and Chun Fan. 2021 · 2021
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The power of scale for parameter-efficient prompt tuning
Brian Lester, Rami Al-Rfou, and Noah Constant. 2021 · 2021
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Backdoor attacks on pre-trained models by layerwise weight poisoning
Linyang Li, Demin Song, Xiaonan Li, Jiehang Zeng, Ruotian Ma, and Xipeng Qiu. 2021 · 2021
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Xiao Liu, Yanan Zheng, Zhengxiao Du, Ming Ding, Yujie Qian, Zhilin Yang, and Jie Tang. 2021 · 2021
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Turn the combination lock: Learnable textual backdoor attacks via word substitution
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Large scale crowdsourcing and characterization of twitter abusive behavior
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Fine-pruning: Defending against backdooring attacks on deep neural networks
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Swag: A large-scale adversarial dataset for grounded commonsense inference
Rowan Zellers, Yonatan Bisk, Roy Schwartz, and Yejin Choi. 2018 · 2018
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Xlnet: Generalized autoregressive pretraining for language understanding
Zhilin Yang, Zihang Dai, Yiming Yang, Jaime Carbonell, Russ R Salakhutdinov, and Quoc V Le. 2019 · 2019
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Tongzhou Wang and Phillip Isola. 2020 · 2020
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Wenkai Yang, Lei Li, Zhiyuan Zhang, Xuancheng Ren, Xu Sun, and Bin He. 2021a
Cited in the paper.
Rethinking stealthiness of backdoor attack against nlp models
Wenkai Yang, Yankai Lin, Peng Li, Jie Zhou, and Xu Sun. 2021b
Cited in the paper.
Fanchao Qi, Yuan Yao, Sophia Xu, Zhiyuan Liu, and Maosong Sun. 2021 · 2021
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Backdoor pre-trained models can transfer to all
Lujia Shen, Shouling Ji, Xuhong Zhang, Jinfeng Li, Jing Chen, Jie Shi, Chengfang Fang, Jianwei Yin, and Ting Wang. 2021 · 2021
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Apple of sodom: Hidden backdoors in superior sentence embeddings via contrastive learning
Xiaoyi Chen, Baisong Xin, Shengfang Zhai, Shiqing Ma, Qingni Shen, and Zhonghai Wu. 2022 · 2022
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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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rspeer/wordfreq: v3.0
Robyn Speer. 2022 · 2022
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Red alarm for pre-trained models: Universal vulnerability to neuron-level backdoor attacks
Zhengyan Zhang, Guangxuan Xiao, Yongwei Li, Tian Lv, Fanchao Qi, Zhiyuan Liu, Yasheng Wang, Xin Jiang, and Maosong Sun. 2023 · 2023
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