69 citations · 71 across the 6 of their papers we have counts for
6 papers
SPEED: Streaming Partition and Parallel Acceleration for Temporal Interaction Graph Embedding
Xi Chen, Yongxiang Liao, Yun Xiong +4
Temporal Interaction Graphs (TIGs) are widely employed to model intricate real-world systems such as financial systems and social networks. To capture the dynamism and interdepende…
RDGSL: Dynamic Graph Representation Learning with Structure Learning
Siwei Zhang, Yun Xiong, Yao Zhang +4
Temporal Graph Networks (TGNs) have shown remarkable performance in learning representation for continuous-time dynamic graphs. However, real-world dynamic graphs typically contain…
iLoRE: Dynamic Graph Representation with Instant Long-term Modeling and Re-occurrence Preservation
Siwei Zhang, Yun Xiong, Yao Zhang +3
Continuous-time dynamic graph modeling is a crucial task for many real-world applications, such as financial risk management and fraud detection. Though existing dynamic graph mode…
Chat-REC: Towards Interactive and Explainable LLMs-Augmented Recommender System
Yunfan Gao, Tao Sheng, Youlin Xiang +3
Large language models (LLMs) have demonstrated their significant potential to be applied for addressing various application tasks. However, traditional recommender systems continue…
TIGER: Temporal Interaction Graph Embedding with Restarts
Yao Zhang, Yun Xiong, Yongxiang Liao +4
Temporal interaction graphs (TIGs), consisting of sequences of timestamped interaction events, are prevalent in fields like e-commerce and social networks. To better learn dynamic…
RuDi: Explaining Behavior Sequence Models by Automatic Statistics Generation and Rule Distillation
Yao Zhang, Yun Xiong, Yiheng Sun +4
Risk scoring systems have been widely deployed in many applications, which assign risk scores to users according to their behavior sequences. Though many deep learning methods with…