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Scaling Laws for Generative Reward Models

Raychev, Angel et al.
arXiv (All) · Papers
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artificial-intelligence
We study generative reward models (GenRMs) as online preference providers for policy optimization in creative writing. Across Qwen3 reward-model sizes from 0.6B to 14B, Thinking judges trained with GRPO have higher static Gold-label accuracy than Answer-Only judges trained with SFT. This ranking oft
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