Foundation models match or approach supervised performance in periodic and cold-start domains but lag in physically constrained systems, while a feature-based router improves accuracy and cuts inference cost versus always using one model class.
Foundts: Comprehensive and unified benchmarking of foundation models for time series forecasting.arXiv preprint arXiv:2410.11802, 2024
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Assessing the Operational Viability of Foundation Models for Time Series Forecasting
Foundation models match or approach supervised performance in periodic and cold-start domains but lag in physically constrained systems, while a feature-based router improves accuracy and cuts inference cost versus always using one model class.