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Carnegie Mellon University
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Discretizing reward models can significantly enhance policy performance by reducing oversensitivity without sacrificing discriminative ability.
Stop wasting tokens on irrelevant questions: reward models that ask about task relevance and user answerability can slash question count by 41% while matching GPT-5's issue resolution rate.
