One-Embedding-Fits-All: Selecting the Best Time-Series Forecasting Model from a Model Zoo
The paper introduces ZooCast, a framework that builds a model zoo of time‑series foundation models and uses a One‑Embedding‑Fits‑All paradigm to embed models and tasks into a unified space, enabling efficient zero‑shot selection that outperforms single models and full‑model ensembles on the GIFT‑Eval benchmark while remaining computationally lightweight.
