3 citations · 4 across the 6 of their papers we have counts for
6 papers
Task-Aware Retrieval Augmentation for Dynamic Recommendation
Zhen Tao, Xinke Jiang, Qingshuai Feng +6
Dynamic recommendation systems aim to provide personalized suggestions by modeling temporal user-item interactions across time-series behavioral data. Recent studies have leveraged…
On the Cross-type Homophily of Heterogeneous Graphs: Understanding and Unleashing
Zhen Tao, Ziyue Qiao, Chaoqi Chen +3
Homophily, the tendency of similar nodes to connect, is a fundamental phenomenon in network science and a critical factor in the performance of graph neural networks (GNNs). While…
Out-of-Distribution Detection with Prototypical Outlier Proxy
Mingrong Gong, Chaoqi Chen, Qingqiang Sun +2
Out-of-distribution (OOD) detection is a crucial task for deploying deep learning models in the wild. One of the major challenges is that well-trained deep models tend to perform o…
PRAGA: Prototype-aware Graph Adaptive Aggregation for Spatial Multi-modal Omics Analysis
Xinlei Huang, Zhiqi Ma, Dian Meng +5
Spatial multi-modal omics technology, highlighted by Nature Methods as an advanced biological technique in 2023, plays a critical role in resolving biological regulatory processes…
Towards Continuous Reuse of Graph Models via Holistic Memory Diversification
Ziyue Qiao, Junren Xiao, Qingqiang Sun +3
This paper addresses the challenge of incremental learning in growing graphs with increasingly complex tasks. The goal is to continuously train a graph model to handle new tasks wh…
Towards Higher-order Topological Consistency for Unsupervised Network Alignment
Qingqiang Sun, Xuemin Lin, Ying Zhang +2
Network alignment task, which aims to identify corresponding nodes in different networks, is of great significance for many subsequent applications. Without the need for labeled an…