Agent4Rec is a recommender system simulator that utilizes 1,000 LLM-empowered generative agents.

These agents are initialized from the 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.