A team is training a language model to solve complex, multi-step word problems. They observe that while the model frequently provides the correct final answer, its step-by-step explanation often contains logical fallacies or incorrect calculations that coincidentally cancel each other out. Which of the following training strategies would be most effective at correcting the model's flawed reasoning process, rather than just its final output?
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Ch.5 Inference - Foundations of Large Language Models
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A team is training a language model to solve complex, multi-step word problems. They observe that while the model frequently provides the correct final answer, its step-by-step explanation often contains logical fallacies or incorrect calculations that coincidentally cancel each other out. Which of the following training strategies would be most effective at correcting the model's flawed reasoning process, rather than just its final output?
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