1 citations · 1 across the 6 of their papers we have counts for
6 papers
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…
Deprecating Benchmarks: Criteria and Framework
Ayrton San Joaquin, Rokas Gipiškis, Leon Staufer +1
As frontier artificial intelligence (AI) models rapidly advance, benchmarks are integral to comparing different models and measuring their progress in different task-specific domai…
Risk Sources and Risk Management Measures in Support of Standards for General-Purpose AI Systems
Rokas Gipiškis, Ayrton San Joaquin, Ze Shen Chin +3
There is an urgent need to identify both short and long-term risks from newly emerging types of Artificial Intelligence (AI), as well as available risk management measures. In resp…
In2Core: Leveraging Influence Functions for Coreset Selection in Instruction Finetuning of Large Language Models
Ayrton San Joaquin, Bin Wang, Zhengyuan Liu +4
Despite advancements, fine-tuning Large Language Models (LLMs) remains costly due to the extensive parameter count and substantial data requirements for model generalization. Acces…
Applying Multilingual Models to Question Answering (QA)
Ayrton San Joaquin, Filip Skubacz
We study the performance of monolingual and multilingual language models on the task of question-answering (QA) on three diverse languages: English, Finnish and Japanese. We develo…
Understanding How Model Size Affects Few-shot Instruction Prompting
Ayrton San Joaquin, Ardy Haroen
Large Language Models are affected by the phenomena of memorizing and forgetting their training data. But how do these vary by model size? We work towards this question by investig…