Class-imbalanced annotation sets degrade in-context learning, and reweighting demonstration scores by class weights plus a validation-fitted conditional bias term (RCB) recovers most of the loss.
Open-sampling: Exploring out-of-distribution data for re-balancing long-tailed datasets
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Exploring Imbalanced Annotations for Effective In-Context Learning
Class-imbalanced annotation sets degrade in-context learning, and reweighting demonstration scores by class weights plus a validation-fitted conditional bias term (RCB) recovers most of the loss.