Measuring Vision-Language STEM Skills of Neural Models

arXiv:2402.17205v1 Announce Type: cross
Abstract: We introduce a new challenge to test the STEM skills of neural models. The problems in the real world often require solutions, combining knowledge from STEM (science, technology, engineering, and math). Unlike existing datasets, our dataset requires the understanding of multimodal vision-language information of STEM. Our dataset features one of the largest and most comprehensive datasets for the challenge. It includes 448 skills and 1,073,146 questions spanning all STEM subjects. Compared to existing datasets that …

abstract arxiv challenge cs.ai cs.cl cs.lg dataset datasets engineering features information knowledge language math measuring multimodal science skills solutions stem technology test type understanding vision world