17 citations · 22 across the 9 of their papers we have counts for
4 papers · 1 filter
LARES: Latent Reasoning for Sequential Recommendation
Enze Liu, Bowen Zheng, Xiaolei Wang +4
Sequential recommender systems have become increasingly important in real-world applications that model user behavior sequences to predict their preferences. However, existing sequ…
DeepRec: Towards a Deep Dive Into the Item Space with Large Language Model Based Recommendation
Bowen Zheng, Xiaolei Wang, Enze Liu +5
Recently, large language models (LLMs) have been introduced into recommender systems (RSs), either to enhance traditional recommendation models (TRMs) or serve as recommendation ba…
Search-Based Interaction For Conversation Recommendation via Generative Reward Model Based Simulated User
Xiaolei Wang, Chunxuan Xia, Junyi Li +5
Conversational recommendation systems (CRSs) use multi-turn interaction to capture user preferences and provide personalized recommendations. A fundamental challenge in CRSs lies i…
Alleviating the Long-Tail Problem in Conversational Recommender Systems
Zhipeng Zhao, Kun Zhou, Xiaolei Wang +4
Conversational recommender systems (CRS) aim to provide the recommendation service via natural language conversations. To develop an effective CRS, high-quality CRS datasets are ve…