Machine Generated Text: A Comprehensive Survey of Threat Models and Detection Methods. (arXiv:2210.07321v1 [cs.CL])

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