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WorldCuisines is a large‑scale multilingual and multicultural visual question answering (VQA) benchmark that focuses on cross‑cultural understanding through global cuisines. The dataset comprises text‑image pairs in 30 languages and dialects, spanning nine language families, and contains over one million data points, making it the largest multicultural VQA benchmark to date. It includes two primary tasks: dish name prediction and location prediction. The construction process involves dish selection, metadata annotation, quality assurance, and data compilation. Two evaluation subsets (12,000 and 60,000 instances) and one training set (1,080,000 instances) are provided.
