Asking models to show their work unlocks reasoning abilities that are invisible under standard prompting — chain-of-thought is a capability elicitation technique, not a training method.
Shows that prompting language models to produce intermediate reasoning steps before answering dramatically improves performance on arithmetic, commonsense, and symbolic reasoning tasks. The effect scales with model size.