Over the past two years, EleutherAI has established itself as a radically novel 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 has 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. [Paper]

Citation: Jason Phang, Herbie Bradley, Leo Gao, Louis Castricato, Stella Biderman EleutherAI: Going Beyond "Open Science" to "Science in the Open". Workshop on Broadening Research Collaborations in ML, NeurIPS 2022.