Leveraging Large Language Models and Bayesian Optimization for Efficient Natural Language Preference Elicitation in Conversational Recommendation Systems
Combining large language models with Bayesian optimization techniques can enable efficient and strategic natural language preference elicitation dialogues to quickly identify a user's top item preferences in cold-start settings.