in time series forecasting and achieve SOT A results, these two papers investigate different problems of time series

As for causal convolution, both papers have their own motivations (robustness V .S. quick response) to use it and utilize Transformer networks to outperform existing works. We plan to add ablation study to illustrate this in the new version. Rolling window: It is used in [3], [6] and [17], our main baselines. Note that loss function, split procedure and some other details are the same as [3] for fair comparisons. The window selection procedures and other details are elaborated in Appendix A.2.