activity
20242026
collaborators

9 papers

cs.LG2026

Capabilities Ain't All You Need: Measuring Propensities in AI

Daniel Romero-Alvarado, Fernando Martínez-Plumed, Lorenzo Pacchiardi +11

AI evaluation has primarily focused on measuring capabilities, with formal approaches inspired from Item Response Theory (IRT) being increasingly applied. Yet propensities - the te…

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.CY2026

Personalized Safety in LLMs: A Benchmark and A Planning-Based Agent Approach

Yuchen Wu, Edward Sun, Kaijie Zhu +4

Large language models (LLMs) typically generate identical or similar responses for all users given the same prompt, posing serious safety risks in high-stakes applications where us…

cs.AI2025

Evaluating Generalization Capabilities of LLM-Based Agents in Mixed-Motive Scenarios Using Concordia

Chandler Smith, Marwa Abdulhai, Manfred Diaz +83

Large Language Model (LLM) agents have demonstrated impressive capabilities for social interaction and are increasingly being deployed in situations where they might engage with bo…

cs.AI2025

Psychometric Personality Shaping Modulates Capabilities and Safety in Language Models

Stephen Fitz, Peter Romero, Steven Basart +2

Large Language Models increasingly mediate high-stakes interactions, intensifying research on their capabilities and safety. While recent work has shown that LLMs exhibit consisten…