6 citations · 17 across the 17 of their papers we have counts for
7 papers · 1 filter
DRDT: Dynamic Reflection with Divergent Thinking for LLM-based Sequential Recommendation
Yu Wang, Zhiwei Liu, Jianguo Zhang +3
The rise of Large Language Models (LLMs) has sparked interest in their application to sequential recommendation tasks as they can provide supportive item information. However, due…
Graph Neural Ordinary Differential Equations-based method for Collaborative Filtering
Ke Xu, Yuanjie Zhu, Weizhi Zhang +1
Graph Convolution Networks (GCNs) are widely considered state-of-the-art for collaborative filtering. Although several GCN-based methods have been proposed and achieved state-of-th…
Multi-view Graph Convolution for Participant Recommendation
Xiaolong Liu, Liangwei Yang, Chen Wang +3
Social networks have become essential for people's lives. The proliferation of web services further expands social networks at an unprecedented scale, leading to immeasurable comme…
Group-Aware Interest Disentangled Dual-Training for Personalized Recommendation
Xiaolong Liu, Liangwei Yang, Zhiwei Liu +4
Personalized recommender systems aim to predict users' preferences for items. It has become an indispensable part of online services. Online social platforms enable users to form g…
Unified Pretraining for Recommendation via Task Hypergraphs
Mingdai Yang, Zhiwei Liu, Liangwei Yang +4
Although pretraining has garnered significant attention and popularity in recent years, its application in graph-based recommender systems is relatively limited. It is challenging…
Knowledge Graph Context-Enhanced Diversified Recommendation
Xiaolong Liu, Liangwei Yang, Zhiwei Liu +4
The field of Recommender Systems (RecSys) has been extensively studied to enhance accuracy by leveraging users' historical interactions. Nonetheless, this persistent pursuit of acc…
Collaborative Semantic Alignment in Recommendation Systems
Chen Wang, Liangwei Yang, Zhiwei Liu +4
Traditional recommender systems primarily leverage identity-based (ID) representations for users and items, while the advent of pre-trained language models (PLMs) has introduced ri…