EleutherAI: Going Beyond "Open Science" to "Science in the Open"
Abstract
Over the past two years, EleutherAI has established itself as a radical initiative aimed at both promoting open-source research and conducting research in a transparent, openly accessible and collaborative manner. EleutherAI's approach to research goes beyond transparency; by doing research entirely in public, anyone in the world can observe and contribute at every stage. Our work has been received positively and resulted in several high-impact projects in Natural Language Processing and other fields. In this paper, we describe our experience doing public-facing machine learning research, the benefits we believe this approach brings, and the pitfalls we have encountered.
Cite
Text
Phang et al. "EleutherAI: Going Beyond "Open Science" to "Science in the Open"." NeurIPS 2022 Workshops: WBRC, 2022.Markdown
[Phang et al. "EleutherAI: Going Beyond "Open Science" to "Science in the Open"." NeurIPS 2022 Workshops: WBRC, 2022.](https://mlanthology.org/neuripsw/2022/phang2022neuripsw-eleutherai/)BibTeX
@inproceedings{phang2022neuripsw-eleutherai,
title = {{EleutherAI: Going Beyond "Open Science" to "Science in the Open"}},
author = {Phang, Jason and Bradley, Herbie and Gao, Leo and Castricato, Louis J. and Biderman, Stella},
booktitle = {NeurIPS 2022 Workshops: WBRC},
year = {2022},
url = {https://mlanthology.org/neuripsw/2022/phang2022neuripsw-eleutherai/}
}