13 citations · 17 across the 4 of their papers we have counts for
4 papers
STLLM-DF: A Spatial-Temporal Large Language Model with Diffusion for Enhanced Multi-Mode Traffic System Forecasting
Zhiqi Shao, Haoning Xi, Haohui Lu +3
The rapid advancement of Intelligent Transportation Systems (ITS) presents challenges, particularly with missing data in multi-modal transportation and the complexity of handling d…
ST-Mamba: Spatial-Temporal Selective State Space Model for Traffic Flow Prediction
Zhiqi Shao, Michael G. H. Bell, Ze Wang +3
Traffic flow prediction, a critical aspect of intelligent transportation systems, has been increasingly popular in the field of artificial intelligence, driven by the availability…
ST-MambaSync: The Complement of Mamba and Transformers for Spatial-Temporal in Traffic Flow Prediction
Zhiqi Shao, Xusheng Yao, Ze Wang +1
Accurate traffic flow prediction is crucial for optimizing traffic management, enhancing road safety, and reducing environmental impacts. Existing models face challenges with long…
CCDSReFormer: Traffic Flow Prediction with a Criss-Crossed Dual-Stream Enhanced Rectified Transformer Model
Zhiqi Shao, Michael G. H. Bell, Ze Wang +3
Accurate, and effective traffic forecasting is vital for smart traffic systems, crucial in urban traffic planning and management. Current Spatio-Temporal Transformer models, despit…