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Agent4Rec is a recommender system simulator that utilizes 1,000 LLM-empowered generative agents. These agents are initialized from the [MovieLens-1M](https://grouplens.org/datasets/movielens/1m/) dataset, embodying varied social traits and preferences. Each agent interacts with personalized movie recommendations in a page-by-page manner and undertakes various actions such as watching, rating, evaluating, exiting, and interviewing.