215 citations · 516 across the 30 of their papers we have counts for
6 papers · 1 filter
Words as Gatekeepers: Measuring Discipline-specific Terms and Meanings in Scholarly Publications
Li Lucy, Jesse Dodge, David Bamman +1
Scholarly text is often laden with jargon, or specialized language that can facilitate efficient in-group communication within fields but hinder understanding for out-groups. In th…
BLOOM: A 176B-Parameter Open-Access Multilingual Language Model
BigScience Workshop, :, Teven Le Scao +391
Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to wi…
Measuring the Carbon Intensity of AI in Cloud Instances
Jesse Dodge, Taylor Prewitt, Remi Tachet Des Combes +7
By providing unprecedented access to computational resources, cloud computing has enabled rapid growth in technologies such as machine learning, the computational demands of which…
Modeling the Machine Learning Multiverse
Samuel J. Bell, Onno P. Kampman, Jesse Dodge +1
Amid mounting concern about the reliability and credibility of machine learning research, we present a principled framework for making robust and generalizable claims: the multiver…
Data Governance in the Age of Large-Scale Data-Driven Language Technology
Yacine Jernite, Huu Nguyen, Stella Biderman +18
The recent emergence and adoption of Machine Learning technology, and specifically of Large Language Models, has drawn attention to the need for systematic and transparent manageme…
Staged Training for Transformer Language Models
Sheng Shen, Pete Walsh, Kurt Keutzer +3
The current standard approach to scaling transformer language models trains each model size from a different random initialization. As an alternative, we consider a staged training…