4.3k citations · 4.4k across the 3 of their papers we have counts for
3 papers
cs.CL2022★ 4.3k cited
Training language models to follow instructions with human feedback
Long Ouyang, Jeff Wu, Xu Jiang +17
Making language models bigger does not inherently make them better at following a user's intent. For example, large language models can generate outputs that are untruthful, toxic,…
cs.CL2021★ 68 cited
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…
cs.AI2017
Pedagogical learning
Long Ouyang, Michael C. Frank
A common assumption in machine learning is that training data are i.i.d. samples from some distribution. Processes that generate i.i.d. samples are, in a sense, uninformative---the…