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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.
LLMs learn in a surprisingly consistent and predictable order, with simpler skills reliably emerging before more complex ones, regardless of model size.