ScenarioDiff: a scenario-level guidance framework for multimodal time series forecasting; extended version shows how textual context signals can guide forecasting.
Read the original at arxiv.org→arXiv:2608.17164v1 Announce Type: new Abstract: Textual context such as news, reports, and logs can provide valuable signals for time series forecasting, especially when future dynamics are driven by external events...
Original headline: "SCENARIODIFF: A Scenario-level Guidance Framework for Multimodal Time Series Forecasting--Extended Version"
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- Aug 19, 04:00 UTC arXiv cs.LG lead source SCENARIODIFF: A Scenario-level Guidance Framework for Multimodal Time Series Forecasting--Extended Version