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Time series foundation models evaluated for zero-shot crowd forecasting

By PulseAugur Editorial · [1 sources] ·

Researchers have evaluated the effectiveness of pretrained time series foundation models for zero-shot forecasting of pedestrian flow during special events. The study, using the SAIL2025 event as a case study, assessed two such models to determine their reliability in providing probabilistic forecasts without extensive retraining. The findings offer practical guidance for crowd managers on when these zero-shot forecasts can be operationally dependable, especially for capturing sudden volatility and tail risks. AI

IMPACT Provides insights into the reliability of zero-shot forecasting for operational decision-making in crowd management.

RANK_REASON Research paper evaluating foundation models for a specific forecasting task. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Time series foundation models evaluated for zero-shot crowd forecasting

COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · Ziteng Li, Yanan Xin, Tina Comes, Serge Hoogendoorn ·

    Towards Reliable Zero-Shot Crowd Forecasting: Evaluating Time Series Foundation Models for Special Event Pedestrian Forecasting

    arXiv:2607.17758v1 Announce Type: new Abstract: Managing massive crowds during infrequent special events requires reliable real-time pedestrian-flow forecasting to ensure public safety and operational efficiency. However, supervised forecasting methods face limitations in these c…

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