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An engineer is creating a prompt that includes several examples of a math word problem followed by a step-by-step solution. The goal is for the model to learn this reasoning pattern. However, the model's final answers are often buried within its explanatory text, making them hard to extract automatically. The engineer modifies each example by placing the token #### immediately before the final numerical answer. Why is this modification an effective strategy?

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Updated 2025-09-26

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Ch.3 Prompting - Foundations of Large Language Models

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