arXiv Machine Learning
TAC-Time: Texts as Channels For Multimodal Time Series Forecasting
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Spectral Text Fusion: A Frequency-Aware Approach to Multimodal Time-Series Forecasting
arXiv:2602. 01588v3 Announce Type: replace-cross Abstract: Multimodal time series forecasting is crucial in real-world applications, where decisions depend on both numerical data and contextual signals.
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Rethinking Multimodal Time-Series Forecasting Evaluation
arXiv:2607. 06973v1 Announce Type: new Abstract: We introduce a new context-enriched, multimodal time series forecasting benchmark, TimesX.
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Semantics or Structure? Auditing Text Sensitivity in Multimodal Time-Series Forecasting
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arXiv AI
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arXiv AI
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InstructTime++: Time Series Classification with Multimodal Language Modeling via Implicit Feature Enhancement
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