A self-alignment prompt pipeline (SHARP) generated roughly 190,000 verifiable STEM problems that, when used to distill or RL-train 7B models, improved GPQA Diamond accuracy in the reported runs.
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SHARP: Synthesizing High-quality Aligned Reasoning Problems for Large Reasoning Models Reinforcement Learning
A self-alignment prompt pipeline (SHARP) generated roughly 190,000 verifiable STEM problems that, when used to distill or RL-train 7B models, improved GPQA Diamond accuracy in the reported runs.