AI Research
TimeOmni-o1: Bidirectionally Coupling Time Series Foundation Models and LLMs for Multimodal Reasoning and Forecasting
A framework links time-series foundation models and language models for multimodal tasks
Time series from real-world systems are often accompanied by text, such as a report on an event that affects them.
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ArXiv CS.CL
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2 min
ArXiv CS.CL
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Generated insight by OnAirToday AI
Real-world time series can come with text describing events that influence their behavior, so combining both data types may support richer analysis. The work’s focus on bidirectional coupling points to an approach for connecting time-series models with language models in reasoning and forecasting tasks.
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