VaryST: Generalizable Spatio-Temporal Forecasting Beyond the Closed-World Setting.

arXiv:2610.19813v1 Announce Type: cross Abstract: Spatio-temporal forecasting is fundamental to many real-world systems, yet deployment environments are inherently varying: temporal distributions may evolve, spatial domains may change, and observation availabi