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We introduce EUREKA, an ensemble-based approach for performing automaticeuphemism detection. We (1) identify and correct potentially mislabelled rowsin the dataset, (2) curate an expanded corpus called EuphAug, (3) leveragemodel representations of Potentially Euphemistic Terms (PETs), and (4) exploreusing representations of semantically close sentences to aid in classification.Using our augmented dataset and kNN-based methods, EUREKA was able to achievestate-of-the-art results on the public leaderboard of the Euphemism DetectionShared Task, ranking first with a macro F1 score of 0.881. Our code isavailable at https://github.com/sedrickkeh/EUREKA.

EUREKA: EUphemism Recognition Enhanced through Knn-based methods and Augmentation