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Textual backdoor attacks pose a practical threat to existing systems, as they can compromise the model by inserting imperceptible triggers into inputs and manipulating labels in the training dataset.
Language models are few-shot learners
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Character-level convolutional networks for text classification
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Transferability in machine learning: from phenomena to black-box attacks using adversarial samples
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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
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Generating natural language adversarial examples
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Trojaning attack on neural networks
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Poison frogs! targeted clean-label poisoning attacks on neural networks
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GLUE: A multi-task benchmark and analysis platform for natural language understanding
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BERT: Pre-training of deep bidirectional transformers for language understanding
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Language models are unsupervised multitask learners
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Sentence-bert: Sentence embeddings using siamese bert-networks
Nils Reimers and Iryna Gurevych. 2019 · 2019
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Weight poisoning attacks on pretrained models
Keita Kurita, Paul Michel, and Graham Neubig. 2020 · 2020
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Hidden backdoors in human-centric language models
Shaofeng Li, Hui Liu, Tian Dong, Benjamin Zi Hao Zhao, Minhui Xue, Haojin Zhu, and Jialiang Lu. 2021b · 2021
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BFClass: A backdoor-free text classification framework
Zichao Li, Dheeraj Mekala, Chengyu Dong, and Jingbo Shang. 2021c · 2021
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ONION: A simple and effective defense against textual backdoor attacks
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Findings of the WMT 2021 shared task on large-scale multilingual machine translation
Guillaume Wenzek, Vishrav Chaudhary, Angela Fan, Sahir Gomez, Naman Goyal, Somya Jain, Douwe Kiela, Tristan Thrush, and Francisco Guzmán. 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. 2021c · 2021
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BART: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension
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BERT-ATTACK: Adversarial attack against BERT using BERT
Linyang Li, Ruotian Ma, Qipeng Guo, Xiangyang Xue, and Xipeng Qiu. 2020 · 2020
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Multilingual denoising pre-training for neural machine translation
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A survey of weight vector adjustment methods for decomposition-based multiobjective evolutionary algorithms
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Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu. 2020 · 2020
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Clear: Contrastive learning for sentence representation
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Badnl: Backdoor attacks against nlp models
Xiaoyi Chen, Ahmed Salem, Michael Backes, Shiqing Ma, and Yang Zhang. 2021 · 2021
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Openattack: An open-source textual adversarial attack toolkit
Guoyang Zeng, Fanchao Qi, Qianrui Zhou, Tingji Zhang, Bairu Hou, Yuan Zang, Zhiyuan Liu, and Maosong Sun. 2021 · 2021
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Kallima: A clean-label framework for textual backdoor attacks
X. Chen, Y. Dong, Z. Sun, S. Zhai, Q. Shen, and Z. Wu. 2022 · 2022
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Triggerless backdoor attack for NLP tasks with clean labels
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Training language models to follow instructions with human feedback
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A survey on backdoor attack and defense in natural language processing
Xuan Sheng, Zhaoyang Han, Piji Li, and Xiangmao Chang. 2022 · 2022
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A word is worth a thousand dollars: Adversarial attack on tweets fools stock prediction
Yong Xie, Dakuo Wang, Pin-Yu Chen, Jinjun Xiong, Sijia Liu, and Oluwasanmi Koyejo. 2022 · 2022
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SHARP: Search-based adversarial attack for structured prediction
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