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cs.IR2026
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…
cs.IR2025★ 8 cited
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…
cs.IR2025
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…