MathCritique-76k
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资源简介：
To train critique models capable of delivering step-level supervision and constructive feedback for reasoning, we introduce AutoMathCritique—an automated and scalable framework for collecting critique data. This framework consists of three main stages: flawed reasoning path construction, critique generation, and data filtering. Using AutoMathCritique, we create a dataset containing $76,321$ samples named MathCritique-76k.
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IEEE DataPort创建时间：
2025-01-09
