8 citations · 9 across the 4 of their papers we have counts for
4 papers
From Topical Relevance to Answerability: Entailment Distillation for Conversational Retrieval
Shuai Qin, Guojia An, Weikang Guo +4
Existing conversational retrievers commonly treat topical relevance as a proxy for answerability. However, a passage that closely matches the dialogue context is not necessarily th…
MSCRS: Multi-modal Semantic Graph Prompt Learning Framework for Conversational Recommender Systems
Yibiao Wei, Jie Zou, Weikang Guo +3
Conversational Recommender Systems (CRSs) aim to provide personalized recommendations by interacting with users through conversations. Most existing studies of CRS focus on extract…
Beyond Whole Dialogue Modeling: Contextual Disentanglement for Conversational Recommendation
Guojia An, Jie Zou, Jiwei Wei +3
Conversational recommender systems aim to provide personalized recommendations by analyzing and utilizing contextual information related to dialogue. However, existing methods typi…
Multi-Type Context-Aware Conversational Recommender Systems via Mixture-of-Experts
Jie Zou, Cheng Lin, Weikang Guo +4
Conversational recommender systems enable natural language conversations and thus lead to a more engaging and effective recommendation scenario. As the conversations for recommende…