Boosting Few-Shot and Zero-Shot Text Classification via Anchor Generation and Classification Reframing

An effective method that breaks out the limitations of seen classes by using generated samples as category anchors and reframing the multi-class classification task as a binary classification problem, leading to substantial performance improvements in few-shot and zero-shot text classification tasks.