9 citations · 15 across the 6 of their papers we have counts for
4 papers · 1 filter
A Scaling Law for Token Efficiency in LLM Fine-Tuning Under Fixed Compute Budgets
Ryan Lagasse, Aidan Kierans, Avijit Ghosh +1
We introduce a scaling law for fine-tuning large language models (LLMs) under fixed compute budgets that explicitly accounts for data composition. Conventional approaches measure t…
Catastrophic Liability: Managing Systemic Risks in Frontier AI Development
Aidan Kierans, Kaley Rittichier, Utku Sonsayar +1
As artificial intelligence systems grow more capable and autonomous, frontier AI development poses potential systemic risks that could affect society at a massive scale. Current pr…
Stop treating `AGI' as the north-star goal of AI research
Borhane Blili-Hamelin, Christopher Graziul, Leif Hancox-Li +13
The AI research community plays a vital role in shaping the scientific, engineering, and societal goals of AI research. In this position paper, we argue that focusing on the highly…
Fully Autonomous AI Agents Should Not be Developed
Margaret Mitchell, Avijit Ghosh, Alexandra Sasha Luccioni +1
This paper argues that fully autonomous AI agents should not be developed. In support of this position, we build from prior scientific literature and current product marketing to d…