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cs.CL2024
UrbanGPT: Spatio-Temporal Large Language Models
Zhonghang Li, Lianghao Xia, Jiabin Tang +5
Spatio-temporal prediction aims to forecast and gain insights into the ever-changing dynamics of urban environments across both time and space. Its purpose is to anticipate future…
cs.CL2024
HiGPT: Heterogeneous Graph Language Model
Jiabin Tang, Yuhao Yang, Wei Wei +4
Heterogeneous graph learning aims to capture complex relationships and diverse relational semantics among entities in a heterogeneous graph to obtain meaningful representations for…
cs.CL2024
GraphGPT: Graph Instruction Tuning for Large Language Models
Jiabin Tang, Yuhao Yang, Wei Wei +5
Graph Neural Networks (GNNs) have evolved to understand graph structures through recursive exchanges and aggregations among nodes. To enhance robustness, self-supervised learning (…