59 citations · 264 across the 38 of their papers we have counts for
5 papers · 1 filter
CoRAL: Collaborative Retrieval-Augmented Large Language Models Improve Long-tail Recommendation
Junda Wu, Cheng-Chun Chang, Tong Yu +4
The long-tail recommendation is a challenging task for traditional recommender systems, due to data sparsity and data imbalance issues. The recent development of large language mod…
Foundation Models for Recommender Systems: A Survey and New Perspectives
Chengkai Huang, Tong Yu, Kaige Xie +3
Recently, Foundation Models (FMs), with their extensive knowledge bases and complex architectures, have offered unique opportunities within the realm of recommender systems (RSs).…
Hierarchical Conversational Preference Elicitation with Bandit Feedback
Jinhang Zuo, Songwen Hu, Tong Yu +3
The recent advances of conversational recommendations provide a promising way to efficiently elicit users' preferences via conversational interactions. To achieve this, the recomme…
Comparison-based Conversational Recommender System with Relative Bandit Feedback
Zhihui Xie, Tong Yu, Canzhe Zhao +1
With the recent advances of conversational recommendations, the recommender system is able to actively and dynamically elicit user preference via conversational interactions. To ac…
Bundle MCR: Towards Conversational Bundle Recommendation
Zhankui He, Handong Zhao, Tong Yu +3
Bundle recommender systems recommend sets of items (e.g., pants, shirt, and shoes) to users, but they often suffer from two issues: significant interaction sparsity and a large out…