15 citations · 47 across the 26 of their papers we have counts for
5 papers · 1 filter
Direction for Detection: A Survey of Automated Vulnerability Detection and all of its Pain Points
Dan Ristea, Shae McFadden, Ezzeldin Shereen +4
Security vulnerabilities in software can have severe consequences; however, manual vulnerability detection is costly and does not scale, especially as agentic coding frameworks inc…
International Scientific Report on the Safety of Advanced AI (Interim Report)
Yoshua Bengio, Sören Mindermann, Daniel Privitera +41
This is the interim publication of the first International Scientific Report on the Safety of Advanced AI. The report synthesises the scientific understanding of general-purpose AI…
Inherently Interpretable and Uncertainty-Aware Models for Online Learning in Cyber-Security Problems
Benjamin Kolicic, Alberto Caron, Chris Hicks +1
In this paper, we address the critical need for interpretable and uncertainty-aware machine learning models in the context of online learning for high-risk industries, particularly…
Fairness with Exponential Weights
Stephen Pasteris, Chris Hicks, Vasilios Mavroudis
Motivated by the need to remove discrimination in certain applications, we develop a meta-algorithm that can convert any efficient implementation of an instance of Hedge (or equiva…
HonestCyberEval: An AI Cyber Risk Benchmark for Automated Software Exploitation
Dan Ristea, Vasilios Mavroudis
We introduce HonestCyberEval, a new benchmark for assessing AI models' capabilities and risks in automated software exploitation, focusing on their ability to detect and exploit vu…