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Event Signature Transfer: Model-Agnostic Forecast Scenario Construction from Historical Events

arXiv · AI, language, vision and robotics · article · Sep 19, 2026 · UTC

Forecasters often know an event is imminent but not the shape, size, or timing of its effect. We introduce Event Signature Transfer (EST), a training-free, model-agnostic operator that turns a completed past event into an explicit forecast scenario. EST removes a source event's own trend and seasonality, then scales and retimes the remaining event signature onto a native forecast, preserving the forecast's linked structure and reducing to it exactly at zero strength. Because it reads only output quantiles, EST applies to any quantile forecaster, with no training, no model internals, at transfe

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Evidence & attribution

First collected: 2026-09-23T10:01:48.231Z. This is not the publication date.