2 citations · 4 across the 5 of their papers we have counts for
5 papers
Improving Conversational Recommendation with Contextual Adaptation of External Recommenders and LLM-based Reranking
Chuang Li, Weida Liang, Hengchang Hu +4
We tackle the challenge of integrating large language models (LLMs) with external recommender systems to enhance domain expertise in conversational recommendation (CRS). Current LL…
Incorporating External Knowledge and Goal Guidance for LLM-based Conversational Recommender Systems
Chuang Li, Yang Deng, Hengchang Hu +2
This paper aims to efficiently enable large language models (LLMs) to use external knowledge and goal guidance in conversational recommender system (CRS) tasks. Advanced LLMs (e.g.…
Lightweight Modality Adaptation to Sequential Recommendation via Correlation Supervision
Hengchang Hu, Qijiong Liu, Chuang Li +1
In Sequential Recommenders (SR), encoding and utilizing modalities in an end-to-end manner is costly in terms of modality encoder sizes. Two-stage approaches can mitigate such conc…
UNO-DST: Leveraging Unlabelled Data in Zero-Shot Dialogue State Tracking
Chuang Li, Yan Zhang, Min-Yen Kan +1
Previous zero-shot dialogue state tracking (DST) methods only apply transfer learning, ignoring unlabelled data in the target domain. We transform zero-shot DST into few-shot DST b…
A Conversation is Worth A Thousand Recommendations: A Survey of Holistic Conversational Recommender Systems
Chuang Li, Hengchang Hu, Yan Zhang +2
Conversational recommender systems (CRS) generate recommendations through an interactive process. However, not all CRS approaches use human conversations as their source of interac…