Artificial Intelligence / Machine Learning
Chain of Thought Reasoning
A prompting technique that encourages large language models to generate intermediate steps or logical sequences before arriving at a final answer.
Explanation
Chain of Thought (CoT) reasoning is a method used to improve the performance of large language models (LLMs) on complex tasks such as arithmetic, commonsense reasoning, and symbolic manipulation. By prompting the model to "think step-by-step," it breaks down a multi-step problem into smaller, manageable parts. This process mimics human cognitive processes where a problem is solved through a series of logical deductions rather than a direct mapping from input to output. CoT can be elicited through few-shot prompting, where the model is provided with examples that include reasoning steps, or zero-shot prompting, using specific trigger phrases.