396 citations · 494 across the 9 of their papers we have counts for
Showing cs.CLShow all
2 papers · 1 filter
cs.CL2020★ 37 cited
Learning to summarize from human feedback
Nisan Stiennon, Long Ouyang, Jeff Wu +6
As language models become more powerful, training and evaluation are increasingly bottlenecked by the data and metrics used for a particular task. For example, summarization models…
cs.CL2019★ 396 cited
Fine-Tuning Language Models from Human Preferences
Daniel M. Ziegler, Nisan Stiennon, Jeffrey Wu +5
Reward learning enables the application of reinforcement learning (RL) to tasks where reward is defined by human judgment, building a model of reward by asking humans questions. Mo…