Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
At a glance
Showed that examples with reasoning steps can help language models solve harder problems.
In one paragraph
Showed that giving large language models examples with intermediate reasoning steps can improve their answers to arithmetic, commonsense, and symbolic reasoning problems. The approach became known as chain-of-thought prompting.
