RATL: Learning from Retrieved Residuals for Robust Multivariate Time-Series Forecasting

Retrieval-augmented generation (RAG) complements parametric models with retrieved external evidence.

Retrieval-augmented generation (RAG) complements parametric models with retrieved external evidence. The same idea is attractive for continuous-output regression, but directly reusing retrieved target values is often not robust when samples differ in output level, numerical…