64 citations · 64 across the 3 of their papers we have counts for
3 papers
cs.MM2022
MMGA: Multimodal Learning with Graph Alignment
Xuan Yang, Quanjin Tao, Xiao Feng +3
Multimodal pre-training breaks down the modality barriers and allows the individual modalities to be mutually augmented with information, resulting in significant advances in repre…
cs.LG2022★ 64 cited
DropMessage: Unifying Random Dropping for Graph Neural Networks
Taoran Fang, Zhiqing Xiao, Chunping Wang +3
Graph Neural Networks (GNNs) are powerful tools for graph representation learning. Despite their rapid development, GNNs also face some challenges, such as over-fitting, over-smoot…
cs.SI2022
Who is next: rising star prediction via diffusion of user interest in social networks
Xuan Yang, Yang Yang, Jintao Su +5
Finding items with potential to increase sales is of great importance in online market. In this paper, we propose to study this novel and practical problem: rising star prediction.…