TheoremExplainBench

简介

TheoremExplainBench TheoremExplainBench is a dataset designed to evaluate and improve the ability of large language models (LLMs) to understand and explain mathematical and scientific theorems across multiple domains, through long-form multimodal content (e.g. Manim Videos). It consists of 240 theorems, categorized by difficulty and subject area to enable structured benchmarking. Dataset Details Curated by: Max Ku, Thomas Chong Language(s) (NLP): English License:… See the full description on the dataset page: https://huggingface.co/datasets/TIGER-Lab/TheoremExplainBench.