Chang-Bin Zhong

Modeling Response Uncertainty and Item Relevance in Conversational Recommender Systems

Conversational Recommender Systems (CRSs) aim to extract user preferences from natural language interactions and deliver personalized recommendations through conversations. In multi-turn conversations, these systems often generate low-confidence responses when user intent is unclear, leading to inappropriate replies an...