activity
20242026
most citedGPAI Evaluations Standards Taskforce: Towards Effective AI Governance

2 citations · 2 across the 3 of their papers we have counts for

collaborators

8 papers

cs.LG2026

Open Problems in Frontier AI Risk Management

Marta Ziosi, Miro Plueckebaum, Stephen Casper +26

Frontier AI both amplifies existing risks and introduces qualitatively novel challenges. Not only is there a notable lack of stable scientific consensus resulting from the rapid pa…

cs.CY2026

International AI Safety Report 2026

Yoshua Bengio, Stephen Clare, Carina Prunkl +89

The International AI Safety Report 2026 synthesises the current scientific evidence on the capabilities, emerging risks, and safety of general-purpose AI systems. The report series…

cs.CY2026

The science and practice of proportionality in AI risk evaluations

Carlos Mougan, Lauritz Morlock, Jair Aguirre +19

A global challenge in artificial intelligence (AI) regulation lies in achieving effective risk management without compromising innovation and technical progress. The European Union…

cs.CY2026

Frontier AI Auditing: Toward Rigorous Third-Party Assessment of Safety and Security Practices at Leading AI Companies

Miles Brundage, Noemi Dreksler, Aidan Homewood +45

We outline a vision for frontier AI auditing, which we define as rigorous third-party verification of frontier AI developers' safety and security claims, and evaluation of their sy…

cs.CY2025

Preliminary suggestions for rigorous GPAI model evaluations

Patricia Paskov, Michael J. Byun, Kevin Wei +1

This document presents a preliminary compilation of general-purpose AI (GPAI) evaluation practices that may promote internal validity, external validity and reproducibility. It inc…

cs.AI2025

Recommendations and Reporting Checklist for Rigorous & Transparent Human Baselines in Model Evaluations

Kevin L. Wei, Patricia Paskov, Sunishchal Dev +6

In this position paper, we argue that human baselines in foundation model evaluations must be more rigorous and more transparent to enable meaningful comparisons of human vs. AI pe…