5 citations · 10 across the 6 of their papers we have counts for
6 papers
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…
Large Language Models for Zero-shot Inference of Causal Structures in Biology
Izzy Newsham, Luka Kovačević, Richard Moulange +2
Genes, proteins and other biological entities influence one another via causal molecular networks. Causal relationships in such networks are mediated by complex and diverse mechani…
Towards Safe Multilingual Frontier AI
Artūrs Kanepajs, Vladimir Ivanov, Richard Moulange
Linguistically inclusive LLMs -- which maintain good performance regardless of the language with which they are prompted -- are necessary for the diffusion of AI benefits around th…
Monitoring Human Dependence On AI Systems With Reliance Drills
Rosco Hunter, Richard Moulange, Jamie Bernardi +1
AI systems are assisting humans with increasingly diverse intellectual tasks but are still prone to mistakes. Humans are over-reliant on this assistance if they trust AI-generated…
Towards Responsible Governance of Biological Design Tools
Richard Moulange, Max Langenkamp, Tessa Alexanian +2
Recent advancements in generative machine learning have enabled rapid progress in biological design tools (BDTs) such as protein structure and sequence prediction models. The unpre…
Open-Sourcing Highly Capable Foundation Models: An evaluation of risks, benefits, and alternative methods for pursuing open-source objectives
Elizabeth Seger, Noemi Dreksler, Richard Moulange +19
Recent decisions by leading AI labs to either open-source their models or to restrict access to their models has sparked debate about whether, and how, increasingly capable AI mode…