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https://arxiv.org/abs/2403.02419 Are More LLM Calls All You Need? Towards Scaling Laws of Compound Inference SystemsMany recent state-of-the-art results in language tasks were achieved using compound systems that perform multiple Language Model (LM) calls and aggregate their responses. However, there is little understanding of how the number of LM calls - e.g., when askarxiv.orgMany recent state..

https://arxiv.org/pdf/2305.200500. Abstractoutcome supervision final result에 피드백ㄷ을 제공 process supervisioneach intermediate reasoning step에 피드백을 제공 process supervision significantly outperforms outcome supervision for training models to solve problems from the challenging MATH dataset (PRM이 ORM보다 좋은것의 맥락) 2. Methods   2.1 scope각 모델 scale에서, 모든 솔루션을 생성하기 위해 하나의 고정된 모델을 사용이 모델을 생성기(generator)라고 함강화..

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