Qitai Tan

Weak policies can achieve up to 18.6% better performance with PATS, a training framework that dynamically adapts guidance based on evolving policy needs.

Decomposing traffic signals into regular and fluctuating components, then applying separate temporal modules, dramatically improves traffic forecasting accuracy compared to treating traffic as a unified representation.

Modeling high-order interactions among traffic nodes via prototype-guided hypergraph construction significantly boosts spatiotemporal forecasting accuracy.