4 papers
Cognitive-Aligned Spatio-Temporal Large Language Models For Next Point-of-Interest Prediction
Penglong Zhai, Jie Li, Fanyi Di +9
The next point-of-interest (POI) recommendation task aims to predict the users' immediate next destinations based on their preferences and historical check-ins, holding significant…
Spacetime-GR: A Spacetime-Aware Generative Model for Large Scale Online POI Recommendation
Haitao Lin, Zhen Yang, Jiawei Xue +5
Building upon the strong sequence modeling capability, Generative Recommendation (GR) has gradually assumed a dominant position in the application of recommendation tasks (e.g., vi…
A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation
Penglong Zhai, Yifang Yuan, Fanyi Di +7
Generative retrieval-based recommendation has emerged as a promising paradigm aiming at directly generating the identifiers of the target candidates. However, in large-scale recomm…
HGCL: Hierarchical Graph Contrastive Learning for User-Item Recommendation
Jiawei Xue, Zhen Yang, Haitao Lin +5
Graph Contrastive Learning (GCL), which fuses graph neural networks with contrastive learning, has evolved as a pivotal tool in user-item recommendations. While promising, existing…