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The STEM dataset is a multimodal benchmark for testing neural models on science, technology, engineering, and mathematics (STEM) skills. It contains 448 skills and 1,073,146 questions covering all STEM subjects. Unlike existing datasets, it requires models to understand multimodal visual‑language information and is based on K‑12 curricula. The dataset is split into training, validation, and test sets; the test set’s ground‑truth answers are hidden and can be evaluated via leaderboard submission. Each entry is a multimodal multiple‑choice question with a description, image, options, and the correct answer index.
