4.3k citations · 7.2k across the 45 of their papers we have counts for
3 papers · 1 filter
Recursively Summarizing Books with Human Feedback
Jeff Wu, Long Ouyang, Daniel M. Ziegler +4
A major challenge for scaling machine learning is training models to perform tasks that are very difficult or time-consuming for humans to evaluate. We present progress on this pro…
Evaluating Large Language Models Trained on Code
Mark Chen, Jerry Tworek, Heewoo Jun +55
We introduce Codex, a GPT language model fine-tuned on publicly available code from GitHub, and study its Python code-writing capabilities. A distinct production version of Codex p…
Institutionalising Ethics in AI through Broader Impact Requirements
Carina Prunkl, Carolyn Ashurst, Markus Anderljung +3
Turning principles into practice is one of the most pressing challenges of artificial intelligence (AI) governance. In this article, we reflect on a novel governance initiative by…