56 citations · 60 across the 5 of their papers we have counts for
6 papers
KUAISHOU Explorer LLM-Rec Challenge 2026: Reasoning Generative Recommendation
Jiangxia Cao, Hao Peng, Wenlong Xu +97
Generative recommendation, has been attracted a surge of attentions in industrial and academic research community, towards to build more smart system to build next-generation recom…
Heterophilous Distribution Propagation for Graph Neural Networks
Zhuonan Zheng, Sheng Zhou, Hongjia Xu +6
Graph Neural Networks (GNNs) have achieved remarkable success in various graph mining tasks by aggregating information from neighborhoods for representation learning. The success r…
Revisiting the Message Passing in Heterophilous Graph Neural Networks
Zhuonan Zheng, Yuanchen Bei, Sheng Zhou +6
Graph Neural Networks (GNNs) have demonstrated strong performance in graph mining tasks due to their message-passing mechanism, which is aligned with the homophily assumption that…
A Survey on Graph Condensation
Hongjia Xu, Liangliang Zhang, Yao Ma +3
Analytics on large-scale graphs have posed significant challenges to computational efficiency and resource requirements. Recently, Graph condensation (GC) has emerged as a solution…
Hilbert Distillation for Cross-Dimensionality Networks
Dian Qin, Haishuai Wang, Zhe Liu +3
3D convolutional neural networks have revealed superior performance in processing volumetric data such as video and medical imaging. However, the competitive performance by leverag…
A Comprehensive Survey on Deep Clustering: Taxonomy, Challenges, and Future Directions
Sheng Zhou, Hongjia Xu, Zhuonan Zheng +7
Clustering is a fundamental machine learning task which has been widely studied in the literature. Classic clustering methods follow the assumption that data are represented as fea…