Position: Beyond Model-Centric Prediction -- Agentic Time Series Forecasting

ArXi:2602.01776v4 Announce Type: replace Time series forecasting has traditionally been formulated as a model-centric, static, and single-pass prediction problem that maps historical observations to future values. While this paradigm has driven substantial progress, it proves insufficient in adaptive and multi-turn settings where forecasting requires informative feature extraction, reasoning-driven inference, iterative refinement, and continual adaptation over time.