MATH()

MATH()是由Consequent AI创建的一个数据集，旨在通过功能化的基准测试来评估语言模型的推理能力。该数据集包含5000个问题，目前已有41.2%的问题被转化为功能化形式，以测试模型在未见过的问题上的表现。数据集的访问地址为https://github.com/consequentai/fneval/，用户可以获取到最新的数据集快照和评估代码。MATH()数据集的应用领域主要集中在提高大型语言模型在数学和逻辑推理方面的性能，旨在解决模型在处理复杂推理任务时的不足。

MATH() is a dataset developed by Consequent AI, designed to evaluate the reasoning capabilities of language models via functionalized benchmarking. This dataset comprises 5,000 questions, 41.2% of which have been converted to functionalized forms to test model performance on unseen problems. The dataset is accessible at https://github.com/consequentai/fneval/, where users can obtain the latest dataset snapshots and evaluation code. The MATH() dataset is primarily focused on enhancing the performance of large language models (LLMs) in mathematical and logical reasoning, aiming to address the shortcomings of models when handling complex reasoning tasks.