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BadPre: Task-agnostic Backdoor Attacks to Pre-trained NLP Foundation Models
[article]
2021
arXiv
pre-print
Pre-trained Natural Language Processing (NLP) models can be easily adapted to a variety of downstream language tasks. This significantly accelerates the development of language models. However, NLP models have been shown to be vulnerable to backdoor attacks, where a pre-defined trigger word in the input text causes model misprediction. Previous NLP backdoor attacks mainly focus on some specific tasks. This makes those attacks less general and applicable to other kinds of NLP models and tasks.
arXiv:2110.02467v1
fatcat:fekccp75frauba4fedciefpnni