Tricky logic riddles for LLM reasoning evaluation

This dataset consists of a small collection of logic-based riddles, including tricky questions and some math problems that require lateral thinking, and interpretation of nuanced language.

The purpose of this dataset is to evaluate the reasoning capabilities of large language models (LLMs) when faced with cognitively challenging prompts that simulate real-world ambiguity and trick-based logic. Each riddle has a clearly defined answer, allowing the dataset to be used for qualitative or automated benchmarking of model responses. This problems are commonly known online but do not have a clear source.

本数据集收录了一组小型逻辑谜题，涵盖需运用发散性思维、解读隐晦措辞的刁钻设问与部分数学问题。
本数据集旨在评估大语言模型（Large Language Models, LLMs）在面对模拟现实歧义、带有误导性逻辑的认知挑战性提示词时的推理能力。每道谜题均设有明确的标准答案，使得本数据集可用于对模型输出开展定性分析或自动化基准测试。此类问题在网络上广为流传，但暂无明确的来源出处。