AI RESEARCH
CoRA: Boosting Time Series Foundation Models for Multivariate Forecasting through Correlation-aware Adapter
arXiv CS.AI
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ArXi:2603.21828v1 Announce Type: cross Most existing Time Series Foundation Models (TSFMs) use channel independent modeling and focus on capturing and generalizing temporal dependencies, while neglecting the correlations among channels or overlooking the different aspects of correlations. However, these correlations play a vital role in Multivariate time series forecasting.