1 citations · 1 across the 4 of their papers we have counts for
4 papers · 1 filter
Detecting undisclosed LLM-generated content in parliamentary texts
Minerva Suvanto, Andrea McGlinchey, Peter J. Barclay +1
In this paper, we evaluate the extent of undisclosed LLM-generated content in texts from the parliaments of the United Kingdom and Sweden. In many areas, such as in journalism or i…
Interpretable Text Classification Applied to the Detection of LLM-generated Creative Writing
Minerva Suvanto, Andrea McGlinchey, Mattias Wahde +1
We consider the problem of distinguishing human-written creative fiction (excerpts from novels) from similar text generated by an LLM. Our results show that, while human observers…
Cat and Mouse -- Can Fake Text Generation Outpace Detector Systems?
Andrea McGlinchey, Peter J Barclay
Large language models can produce convincing "fake text" in domains such as academic writing, product reviews, and political news. Many approaches have been investigated for the de…
Using Machine Learning to Distinguish Human-written from Machine-generated Creative Fiction
Andrea Cristina McGlinchey, Peter J Barclay
Following the universal availability of generative AI systems with the release of ChatGPT, automatic detection of deceptive text created by Large Language Models has focused on dom…