arekborucki/Turing-Open-Reasoning

该数据集包含跨物理、数学、生物和化学领域的计算密集型、自包含且明确的STEM推理问题。问题需要多步推理、符号操作、数值精度或基于模拟的验证。这些任务暴露了最先进LLM的失败模式，使该数据集成为评估深度推理的强大基准。每个示例包括：对话ID、领域和子领域、带有LaTeX的严谨问题、确定性答案以及用于模拟或验证的可选Python代码。

This dataset contains computationally intensive, self-contained, and unambiguous STEM reasoning problems across Physics, Mathematics, Biology, and Chemistry. Problems require multi-step reasoning, symbolic manipulation, numerical accuracy, or simulation-based verification. These tasks expose failure modes in state-of-the-art LLMs, making this dataset a strong benchmark for evaluating deep reasoning. Each example includes: conversation_id, domain and sub-domain, a rigorous question with LaTeX, a deterministic answer, and optional Python code for simulation or verification.