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This paper asks whether extrapolating the hidden space distribution of textexamples from one class onto another is a valid inductive bias for dataaugmentation. To operationalize this question, I propose a simple dataaugmentation protocol called "good-enough example extrapolation" (GE3). GE3 islightweight and has no hyperparameters. Applied to three text classificationdatasets for various data imbalance scenarios, GE3 improves performance morethan upsampling and other hidden-space data augmentation methods.

Good-Enough Example Extrapolation