5 citations · 8 across the 5 of their papers we have counts for
5 papers
RABot: Reinforcement-Guided Graph Augmentation for Imbalanced and Noisy Social Bot Detection
Longlong Zhang, Xi Wang, Haotong Du +3
Social bot detection is pivotal for safeguarding the integrity of online information ecosystems. Although recent graph neural network (GNN) solutions achieve strong results, they r…
Distillation-based Scenario-Adaptive Mixture-of-Experts for the Matching Stage of Multi-scenario Recommendation
Ruibing Wang, Shuhan Guo, Haotong Du +1
Multi-scenario recommendation is pivotal for optimizing user experience across diverse contexts. While Multi-gate Mixture-of-Experts (MMOE) thrives in ranking, its transfer to the…
PERSCEN: Learning Personalized Interaction Pattern and Scenario Preference for Multi-Scenario Matching
Haotong Du, Yaqing Wang, Fei Xiong +5
With the expansion of business scales and scopes on online platforms, multi-scenario matching has become a mainstream solution to reduce maintenance costs and alleviate data sparsi…
Customized Subgraph Selection and Encoding for Drug-drug Interaction Prediction
Haotong Du, Quanming Yao, Juzheng Zhang +2
Subgraph-based methods have proven to be effective and interpretable in predicting drug-drug interactions (DDIs), which are essential for medical practice and drug development. Sub…
Search to Pass Messages for Temporal Knowledge Graph Completion
Zhen Wang, Haotong Du, Quanming Yao +1
Completing missing facts is a fundamental task for temporal knowledge graphs (TKGs). Recently, graph neural network (GNN) based methods, which can simultaneously explore topologica…