AI RESEARCH

Stabilizing distribution-free probabilistic forecasts

arXiv CS.LG

ArXi:2605.28531v1 Announce Type: new Multi-step-ahead forecasts are often updated as new observations become available, since shorter forecast horizons typically improve forecast quality. However, such improvements come at the cost of forecast instability, i.e., variability in forecasts for the same target period. This instability can trigger costly changes to plans formulated based on the forecasts and may erode trust in the forecasting system. In this work, we integrate forecast stability alongside forecast quality into the