3 citations · 5 across the 6 of their papers we have counts for
6 papers
FuxiShuffle: An Adaptive and Resilient Shuffle Service for Distributed Data Processing on Alibaba Cloud
Yuhao Lin, Zhipeng Tang, Jiayan Tong +11
Shuffle exchanges intermediate results between upstream and downstream operators in distributed data processing and is usually the bottleneck due to factors such as small random I/…
Exploiting Text Semantics for Few and Zero Shot Node Classification on Text-attributed Graph
Yuxiang Wang, Xiao Yan, Shiyu Jin +6
Text-attributed graph (TAG) provides a text description for each graph node, and few- and zero-shot node classification on TAGs have many applications in fields such as academia an…
Hound: Hunting Supervision Signals for Few and Zero Shot Node Classification on Text-attributed Graph
Yuxiang Wang, Xiao Yan, Shiyu Jin +6
Text-attributed graph (TAG) is an important type of graph structured data with text descriptions for each node. Few- and zero-shot node classification on TAGs have many application…
TreeCSS: An Efficient Framework for Vertical Federated Learning
Qinbo Zhang, Xiao Yan, Yukai Ding +4
Vertical federated learning (VFL) considers the case that the features of data samples are partitioned over different participants. VFL consists of two main steps, i.e., identify t…
Generative and Contrastive Paradigms Are Complementary for Graph Self-Supervised Learning
Yuxiang Wang, Xiao Yan, Chuang Hu +5
For graph self-supervised learning (GSSL), masked autoencoder (MAE) follows the generative paradigm and learns to reconstruct masked graph edges or node features. Contrastive Learn…
BenchTemp: A General Benchmark for Evaluating Temporal Graph Neural Networks
Qiang Huang, Jiawei Jiang, Xi Susie Rao +10
To handle graphs in which features or connectivities are evolving over time, a series of temporal graph neural networks (TGNNs) have been proposed. Despite the success of these TGN…