1 citations · 2 across the 5 of their papers we have counts for
5 papers
Your AI Travel Agent Would Book You a Bullfight: An Agentic Benchmark for Implicit Animal Welfare in Frontier AI Models
Jasmine Brazilek, Joel Christoph, Maheep Chaudhary +4
Previous research has evaluated animal welfare using question-and-answer benchmarks. This study investigates whether these evaluations also hold in agentic settings. The agents may…
Prioritization of Risks from Artificial Intelligence: A Delphi Study of 272 International Experts
Alexander K. Saeri, Jess Graham, Michael Noetel +185
Artificial intelligence poses many risks, ranging from familiar present-day harms to unprecedented and potentially catastrophic ones. Effective risk management requires prioritizat…
LAG-MMLU: Benchmarking Frontier LLM Understanding in Latvian and Giriama
Naome A. Etori, Kevin Lu, Randu Karisa +1
As large language models (LLMs) rapidly advance, evaluating their performance is critical. LLMs are trained on multilingual data, but their reasoning abilities are mainly evaluated…
What do Large Language Models Say About Animals? Investigating Risks of Animal Harm in Generated Text
Arturs Kanepajs, Aditi Basu, Sankalpa Ghose +7
As machine learning systems become increasingly embedded in society, their impact on human and nonhuman life continues to escalate. Technical evaluations have addressed a variety o…
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…