Preprint Open access
RepICL: Reusable In-Context Prediction Across Heterogeneous Representation Spaces
Frozen representations are widely reused for downstream classification, yet each new task typically requires fitting a new predictor. We ask whether the few-shot prediction procedure itself can instead be learned once and reused across datasets and representation spaces. To study this question, we introduce RepShiftBen …