35 citations · 35 across the 3 of their papers we have counts for
3 papers
cs.CY2026
Global Cybercrime Damages: A Baseline for Frontier AI Risk Assessment
Kamilė Lukošiūtė, John Halstead, Luca Righetti
AI companies and governments are increasingly concerned about frontier AI systems enabling cybercrime, yet defining meaningful capability thresholds requires knowing the scale of c…
cs.CR2025
LLM Cyber Evaluations Don't Capture Real-World Risk
Kamilė Lukošiūtė, Adam Swanda
Large language models (LLMs) are demonstrating increasing prowess in cybersecurity applications, creating creating inherent risks alongside their potential for strengthening defens…
cs.HC2022★ 35 cited
Measuring Progress on Scalable Oversight for Large Language Models
Samuel R. Bowman, Jeeyoon Hyun, Ethan Perez +43
Developing safe and useful general-purpose AI systems will require us to make progress on scalable oversight: the problem of supervising systems that potentially outperform us on m…