Towards Retrieval-Augmented Large Language Model-Based Conversational Recommender System

Dayu Yang, Fuli Wang

Abstract: Conversational Recommender Systems (CRS) aim to provide recommendations through multi-turn natural language interactions. Recent LLM-based approaches have shown impressive performance by leveraging large language models (LLMs). However, these systems face several challenges: they struggle to recommend newly listed items, and are prone to hallucinations.

External IDs:dblp:conf/pakdd/YangW25