Fewer yet critical: Reducing Redundant Token Dependencies for Transformer-based Time Series Forecasting

Time series forecasting (TSF) is important in real-world applications. Recently, Transformer-based methods have achieved strong performance by modeling token dependencies through attention mechanisms. However, existing methods are usually trained mainly with prediction error losses, which may cause