A Multi-Resolution Multi-Domain Pre-Training Framework for Universal Traffic Forecasting
This work proposes FlexST, a novel pre-training framework that introduces modularity and adaptivity for traffic modeling, and devise a unified periodic encoding strategy that injects resolution- and domain-aware inductive biases to harmonize periodic inconsistencies across datasets.
Zhou-Yang Liu, Jin-Dong Han, Hao Wang et al.
· 0 citations