96 citations · 246 across the 9 of their papers we have counts for
14 papers
Short Text Pre-training with Extended Token Classification for E-commerce Query Understanding
Haoming Jiang, Tianyu Cao, Zheng Li +6
E-commerce query understanding is the process of inferring the shopping intent of customers by extracting semantic meaning from their search queries. The recent progress of pre-tra…
DiP-GNN: Discriminative Pre-Training of Graph Neural Networks
Simiao Zuo, Haoming Jiang, Qingyu Yin +3
Graph neural network (GNN) pre-training methods have been proposed to enhance the power of GNNs. Specifically, a GNN is first pre-trained on a large-scale unlabeled graph and then…
Semi-Supervised Graph-to-Graph Translation
Tianxiang Zhao, Xianfeng Tang, Xiang Zhang +1
Graph translation is very promising research direction and has a wide range of potential real-world applications. Graph is a natural structure for representing relationship and int…
Graph Structure Learning for Robust Graph Neural Networks
Wei Jin, Yao Ma, Xiaorui Liu +3
Graph Neural Networks (GNNs) are powerful tools in representation learning for graphs. However, recent studies show that GNNs are vulnerable to carefully-crafted perturbations, cal…
Knowing your FATE: Friendship, Action and Temporal Explanations for User Engagement Prediction on Social Apps
Xianfeng Tang, Yozen Liu, Neil Shah +3
With the rapid growth and prevalence of social network applications (Apps) in recent years, understanding user engagement has become increasingly important, to provide useful insig…
Investigating and Mitigating Degree-Related Biases in Graph Convolutional Networks
Xianfeng Tang, Huaxiu Yao, Yiwei Sun +5
Graph Convolutional Networks (GCNs) show promising results for semi-supervised learning tasks on graphs, thus become favorable comparing with other approaches. Despite the remarkab…