How Good Are Time-Series Foundation Models for Pedestrian Crowd Count Forecasting? A Cross-Dataset Comparative Study
Seasonal Naive remains a strong baseline for long-horizon forecasting on high-volume sensors, while trained models can degrade when the next day differs substantially from prior days, and FMs excel in the seasonal and data-rich regime under long-context configuration.
Theivaprakasham Hari, Zi-Teng Li, Ya-Nan Xin et al.
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