Recency Biased Causal Attention for Time-series Forecasting

ArXi:2502.06151v2 Announce Type: replace Recency bias is a useful inductive prior for sequential modeling: it emphasizes nearby observations and can still allow longer-range dependencies. Standard Transformer attention lacks this property, relying on all-to-all interactions that overlook the causal and often local structure of temporal data. We propose a simple mechanism to