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Are You Robert or RoBERTa? Deceiving Online Authorship Attribution Models Using Neural Text Generators. (arXiv:2203.09813v1 [cs.CL])
March 21, 2022, 1:11 a.m. | Keenan Jones, Jason R. C. Nurse, Shujun Li
cs.LG updates on arXiv.org arxiv.org
Recently, there has been a rise in the development of powerful pre-trained
natural language models, including GPT-2, Grover, and XLM. These models have
shown state-of-the-art capabilities towards a variety of different NLP tasks,
including question answering, content summarisation, and text generation.
Alongside this, there have been many studies focused on online authorship
attribution (AA). That is, the use of models to identify the authors of online
texts. Given the power of natural language models in generating convincing
texts, this paper …
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