A multi-objective prompt optimization framework for LLM user simulators in conversational recommender systems improves behavioral alignment with human patterns over baselines.
D2k: Turning historical data into retrievable knowledge for recommender systems,
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Prompt Optimization for User Simulation in Conversational Recommender Systems: A Multi-Objective Framework
A multi-objective prompt optimization framework for LLM user simulators in conversational recommender systems improves behavioral alignment with human patterns over baselines.