83 citations · 121 across the 5 of their papers we have counts for
5 papers
Reinforced Prompt Personalization for Recommendation with Large Language Models
Wenyu Mao, Jiancan Wu, Weijian Chen +3
Designing effective prompts can empower LLMs to understand user preferences and provide recommendations with intent comprehension and knowledge utilization capabilities. Neverthele…
Explainable Sparse Knowledge Graph Completion via High-order Graph Reasoning Network
Weijian Chen, Yixin Cao, Fuli Feng +2
Knowledge Graphs (KGs) are becoming increasingly essential infrastructures in many applications while suffering from incompleteness issues. The KG completion task (KGC) automatical…
Structure-Enhanced Meta-Learning For Few-Shot Graph Classification
Shunyu Jiang, Fuli Feng, Weijian Chen +2
Graph classification is a highly impactful task that plays a crucial role in a myriad of real-world applications such as molecular property prediction and protein function predicti…
CatGCN: Graph Convolutional Networks with Categorical Node Features
Weijian Chen, Fuli Feng, Qifan Wang +4
Recent studies on Graph Convolutional Networks (GCNs) reveal that the initial node representations (i.e., the node representations before the first-time graph convolution) largely…
Graph Convolution Machine for Context-aware Recommender System
Jiancan Wu, Xiangnan He, Xiang Wang +4
The latest advance in recommendation shows that better user and item representations can be learned via performing graph convolutions on the user-item interaction graph. However, s…