90 citations · 140 across the 13 of their papers we have counts for
4 papers · 1 filter
Understanding the limitations of self-supervised learning for tabular anomaly detection
Kimberly T. Mai, Toby Davies, Lewis D. Griffin
While self-supervised learning has improved anomaly detection in computer vision and natural language processing, it is unclear whether tabular data can benefit from it. This paper…
Use of LLMs for Illicit Purposes: Threats, Prevention Measures, and Vulnerabilities
Maximilian Mozes, Xuanli He, Bennett Kleinberg +1
Spurred by the recent rapid increase in the development and distribution of large language models (LLMs) across industry and academia, much recent work has drawn attention to safet…
Susceptibility to Influence of Large Language Models
Lewis D Griffin, Bennett Kleinberg, Maximilian Mozes +4
Two studies tested the hypothesis that a Large Language Model (LLM) can be used to model psychological change following exposure to influential input. The first study tested a gene…
Warning: Humans Cannot Reliably Detect Speech Deepfakes
Kimberly T. Mai, Sergi D. Bray, Toby Davies +1
Speech deepfakes are artificial voices generated by machine learning models. Previous literature has highlighted deepfakes as one of the biggest security threats arising from progr…