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Reasoning models — think before answering
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Frequently Asked Questions

What is Chain-of-Thought Prompting?

A prompting strategy that instructs an LLM to show intermediate reasoning steps before producing a final answer, improving accuracy on complex tasks. Chain-of-Thought (CoT) prompting is a technique introduced by Wei et al. in 2022 that improves LLM reasoning by instructing the model to generate step-by-step intermediate reasoning before reaching a conclusion.

How is Chain-of-Thought Prompting used in practice?

CoT prompting dramatically improves performance on multi-step arithmetic, logical reasoning, and common-sense reasoning tasks where a direct answer without reasoning is error-prone.

Why is Chain-of-Thought Prompting important in AI?

Chain-of-Thought Prompting is a foundational concept in Prompting Technique. A prompting strategy that instructs an LLM to show intermediate reasoning steps before producing a final answer, improving accuracy on complex tasks.

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