Web: http://arxiv.org/abs/2210.07321

Nov. 22, 2022, 2:20 a.m. | Evan Crothers, Nathalie Japkowicz, Herna Viktor

cs.CR updates on arXiv.org arxiv.org

Advances in natural language generation (NLG) have resulted in machine
generated text that is increasingly difficult to distinguish from human
authored text. Powerful open-source models are freely available, and
user-friendly tools democratizing access to generative models are
proliferating. The great potential of state-of-the-art NLG systems is tempered
by the multitude of avenues for abuse. Detection of machine generated text is a
key countermeasure for reducing abuse of NLG models, with significant technical
challenges and numerous open problems. We provide a …

detection machine survey text threat threat models

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