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Shopping MMLU is a large‑scale multi‑task online‑shopping benchmark dataset created by Amazon. It is designed to comprehensively evaluate large language models (LLMs) on multiple shopping‑related tasks. The dataset comprises 57 tasks covering four core shopping skills—concept understanding, knowledge reasoning, user‑behavior alignment, and multilingual capability—totaling 20,799 questions. It was constructed from authentic Amazon data and reformulated into text‑generation tasks to suit LLM solutions. Shopping MMLU is primarily intended for online‑shopping assistants, aiming to improve the shopping experience by reducing task‑specific engineering effort and enabling interactive user dialogues.
