Big-Math 强化学习数学数据集

Big-Math 是一个大规模、高质量的数学数据集，专为强化学习 (Reinforcement Learning, RL) 在语言模型中的应用而设计。该数据集由斯坦福大学和 SynthLabs 的研究人员于 2025 年发布，相关论文成果为「Big-Math: A Large-Scale, High-Quality Math Dataset for Reinforcement Learning in Language Models」。

Big-Math is a large-scale, high-quality mathematics dataset specifically designed for the application of Reinforcement Learning (RL) in language models. This dataset was released in 2025 by researchers from Stanford University and SynthLabs, with its accompanying research paper titled "Big-Math: A Large-Scale, High-Quality Math Dataset for Reinforcement Learning in Language Models".

搜集汇总

背景与挑战

背景概述

Big-Math是一个大规模、高质量的数学数据集，包含超过250k个具有唯一正确答案的数学问题，专为强化学习在语言模型中的应用设计。该数据集由斯坦福大学和SynthLabs的研究人员发布，具有唯一可验证的解决方案、封闭形式的解和开放式问题等特点。