565 citations · 2.2k across the 18 of their papers we have counts for
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cs.CL2021★ 27 cited
A General Language Assistant as a Laboratory for Alignment
Amanda Askell, Yuntao Bai, Anna Chen +19
Given the broad capabilities of large language models, it should be possible to work towards a general-purpose, text-based assistant that is aligned with human values, meaning that…
cs.LG2021★ 26 cited
Scaling Laws for Transfer
Danny Hernandez, Jared Kaplan, Tom Henighan +1
We study empirical scaling laws for transfer learning between distributions in an unsupervised, fine-tuning setting. When we train increasingly large neural networks from-scratch o…