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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 i
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