Hard routing through a Manager model lets specialized Workers handle different data regimes automatically, improving forecasting accuracy while reducing inference costs compared to soft-routing ensemble approaches.
CATF is a forecasting framework that uses a Manager-Worker architecture to predict time-series values when multiple contextual factors (like weather or calendar) influence the data. A Transformer-based Manager intelligently routes each input to a specialized Worker model based on context, allowing workers to automatically specialize without manual data splitting.