most citedA Boundary Tilting Persepective on the Phenomenon of Adversarial Examples

135 citations · 173 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL202329 cited

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…

cs.CL20238 cited

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…

cs.CV2016

Automated detection of smuggled high-risk security threats using Deep Learning

Nicolas Jaccard, Thomas W. Rogers, Edward J. Morton +1

The security infrastructure is ill-equipped to detect and deter the smuggling of non-explosive devices that enable terror attacks such as those recently perpetrated in western Euro…

cs.LG2016135 cited

A Boundary Tilting Persepective on the Phenomenon of Adversarial Examples

Thomas Tanay, Lewis Griffin

Deep neural networks have been shown to suffer from a surprising weakness: their classification outputs can be changed by small, non-random perturbations of their inputs. This adve…

cs.CV20161 cited

Automated X-ray Image Analysis for Cargo Security: Critical Review and Future Promise

Thomas W. Rogers, Nicolas Jaccard, Edward J. Morton +1

We review the relatively immature field of automated image analysis for X-ray cargo imagery. There is increasing demand for automated analysis methods that can assist in the inspec…