5 papers
Can Generative Recommendation Reach Cold Items? A Temporal Perspective on Semantic-ID Generation
Jie Peng, Yanping Zheng, Zhewei Zhe +3
Semantic-ID-based generative recommendation represents items as sequences of shared semantic tokens, enabling token recombination beyond isolated item IDs. However, closed-world re…
TIDFormer: Exploiting Temporal and Interactive Dynamics Makes A Great Dynamic Graph Transformer
Jie Peng, Zhewei Wei, Yuhang Ye
Due to the proficiency of self-attention mechanisms (SAMs) in capturing dependencies in sequence modeling, several existing dynamic graph neural networks (DGNNs) utilize Transforme…
Beyond Leakage and Complexity: Towards Realistic and Efficient Information Cascade Prediction
Jie Peng, Rui Wang, Qiang Wang +4
Information cascade popularity prediction is a key problem in analyzing content diffusion in social networks. However, current related works suffer from three critical limitations:…
GDGB: A Benchmark for Generative Dynamic Text-Attributed Graph Learning
Jie Peng, Jiarui Ji, Runlin Lei +3
Dynamic Text-Attributed Graphs (DyTAGs), which intricately integrate structural, temporal, and textual attributes, are crucial for modeling complex real-world systems. However, mos…
TGB-Seq Benchmark: Challenging Temporal GNNs with Complex Sequential Dynamics
Lu Yi, Jie Peng, Yanping Zheng +5
Future link prediction is a fundamental challenge in various real-world dynamic systems. To address this, numerous temporal graph neural networks (temporal GNNs) and benchmark data…