R. Kazemian

The Impact of Synthetic Data Augmentation on Discourse-Pragmatic Function Classification

Synthetic data augmentation has become a common strategy for addressing class imbalance in NLP, but most approaches focus on the quantity and diversity of generated examples rather than their geometric relationship to real training data. We investigate this question in the context of discourse pragmatic function classi...