Chain of Thought (CoT) prompting is a technique used primarily with large language models (LLMs) to improve their reasoning abilities. Instead of directly asking for an answer, CoT prompting encourages the model to first articulate its reasoning process step-by-step before arriving at a final conclusion. This approach often leads to more accurate and reliable results, especially for complex or multi-step problems. It is commonly used in question answering, mathematical reasoning, and logical inference tasks.
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