CrossLinear: Plug-and-Play Cross-Correlation Embedding for Time Series Forecasting with Exogenous Variables

The paper introduces CrossLinear, a lightweight, linear-based time series forecasting model that effectively captures direct, time-invariant dependencies between endogenous and exogenous variables using a plug-and-play cross-correlation embedding module. Extensive experiments demonstrate its superior performance and generalizability across 12 real-world datasets, addressing overfitting issues and improving short- and long-term forecasting accuracy.