CoT (Chain of Thought) prompting is a newly developed method designed to prompt large language models (LLMs) to explain their reasoning. It encourages the model to generate text that provides a clear chain of thoughts, allowing users to understand how the model arrived at its conclusions. By using CoT prompting, users can gain insights into the decision-making process of the LLM, which can be valuable for understanding its behavior and ensuring transparency in its outputs.
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