CoffeeGitta/difficulty-aime_1983-2024-generations

该数据集是一个针对AIME（美国数学邀请赛，1983-2024年）问题的LLM生成解决方案集合。它包含多个模型（如Qwen2.5-Math、DeepSeek-R1、GPT-OSS-20B等）在不同配置下生成的数学问题解答，覆盖训练、验证和测试分割。数据集中每个条目包括问题陈述、生成的解决方案列表（带分数和成本信息）、成功率、多数投票正确性等字段，旨在用于研究LLM的失败预测，即通过生成前的激活来预测成功。数据集总大小约1.8GB，包含747个训练示例、186个验证示例和30个测试示例（不同模型略有差异）。

Generations Dataset: aime_1983-2024. LLM-generated solutions across train/validation/test splits for multiple models. It contains solutions generated by various models (e.g., Qwen2.5-Math, DeepSeek-R1, GPT-OSS-20B) for AIME (American Invitational Mathematics Examination, 1983-2024) problems, with features such as problem statements, generated solutions (with scores and cost information), success rates, majority vote correctness, etc. The dataset is designed for research on predicting LLM failures from pre-generation activations. Total dataset size is approximately 1.8GB, with 747 training examples, 186 validation examples, and 30 test examples (varies slightly across models).