This paper explores the ability of language models to generate a coherent chain of thought—a series of short sentences that mimic the reasoning process a person might have when responding to a question. Experiments show that inducing a chain of thought via prompting can enable sufficiently large language models to better perform reasoning tasks that otherwise have flat scaling curves.
Came across this today on r/mlscaling and thought I’d put it here since it’s relevant: https://arxiv.org/abs/2201.11903#google