EventTSF: Event-Aware Non-Stationary Time Series Forecasting

ArXi:2508.13434v2 Announce Type: replace-cross Time series forecasting is vital in diverse sectors such as energy and transportation, where non-stationary dynamics are deeply intertwined with external events in other modalities such as texts. However, incorporating natural language-based external events to improve non-stationary forecasting remains largely unexplored, as most approaches still rely on a single modality, resulting in limited contextual knowledge and model underperformance.