Chain-of-Thought Prompting
Date of Addition
17 Oct 2025
A prompt engineering technique that elicits intermediate reasoning steps from language models by instructing them to explain their problem-solving process explicitly before arriving at final answers. This method improves LLM performance on complex tasks requiring multi-step logic, arithmetic reasoning, or sequential decision-making by forcing the model to articulate its cognitive process rather than directly outputting conclusions. Chain-of-thought prompting leverages the model's ability to simulate reasoning narratives that increase accuracy on benchmarks while making outputs more interpretable and verifiable for human reviewers evaluating correctness.
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