65 citations · 111 across the 5 of their papers we have counts for
6 papers
The BigScience ROOTS Corpus: A 1.6TB Composite Multilingual Dataset
Hugo Laurençon, Lucile Saulnier, Thomas Wang +51
As language models grow ever larger, the need for large-scale high-quality text datasets has never been more pressing, especially in multilingual settings. The BigScience workshop,…
The ROOTS Search Tool: Data Transparency for LLMs
Aleksandra Piktus, Christopher Akiki, Paulo Villegas +5
ROOTS is a 1.6TB multilingual text corpus developed for the training of BLOOM, currently the largest language model explicitly accompanied by commensurate data governance efforts.…
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…
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…
Documenting Geographically and Contextually Diverse Data Sources: The BigScience Catalogue of Language Data and Resources
Angelina McMillan-Major, Zaid Alyafeai, Stella Biderman +15
In recent years, large-scale data collection efforts have prioritized the amount of data collected in order to improve the modeling capabilities of large language models. This prio…
A question-answering system for aircraft pilots' documentation
Alexandre Arnold, Gérard Dupont, Félix Furger +2
The aerospace industry relies on massive collections of complex and technical documents covering system descriptions, manuals or procedures. This paper presents a question answerin…