考研理科CoT数据集

考研理科CoT（Chain-of-Thought）数据集面向数学、物理、化学等理科类考研真题与练习题，提供结构化的逐步推理过程标注，适用于训练和评估大语言模型在复杂学科问题上的逻辑推理与解题能力。该数据集不仅可用于构建更精准的教育问答系统和智能辅导工具，还能用于推动通用人工智能在严谨学术场景中的应用，提升模型在高阶认知任务中的表现和可解释性。

The Science-track Chain-of-Thought (CoT) Dataset for the National Postgraduate Entrance Examination focuses on real exam questions and practice problems from disciplines including mathematics, physics, chemistry and other science-related fields. It provides annotated structured step-by-step reasoning processes, and is suitable for training and evaluating the logical reasoning and problem-solving capabilities of large language models (LLMs) on complex disciplinary problems. Moreover, this dataset can not only be used to construct more precise educational question-answering systems and intelligent tutoring tools, but also promote the application of artificial general intelligence (AGI) in rigorous academic scenarios, and enhance the performance and interpretability of models in high-order cognitive tasks.