7 citations · 11 across the 4 of their papers we have counts for
4 papers
HoF-Bench: Rediscovering Real AI-Discovered CVEs Without Frontier Models
Petr Simecek, Elnaz Babayeva, Jiri Balhar +23
LLM-based analyzers have begun finding real vulnerabilities in mature open-source projects: AISLE's analyzer is credited with more than 280 CVEs across 78 projects, including OpenS…
Large language models can consistently generate high-quality content for election disinformation operations
Angus R. Williams, Liam Burke-Moore, Ryan Sze-Yin Chan +7
Advances in large language models have raised concerns about their potential use in generating compelling election disinformation at scale. This study presents a two-part investiga…
Prompto: An open source library for asynchronous querying of LLM endpoints
Ryan Sze-Yin Chan, Federico Nanni, Angus R. Williams +7
Recent surge in Large Language Model (LLM) availability has opened exciting avenues for research. However, efficiently interacting with these models presents a significant hurdle s…
Design choices for productive, secure, data-intensive research at scale in the cloud
Diego Arenas, Jon Atkins, Claire Austin +22
We present a policy and process framework for secure environments for productive data science research projects at scale, by combining prevailing data security threat and risk prof…