Few Shot Text Classification

Few-Shot Text Classification is an important task in the field of natural language processing, aimed at predicting the semantic label of given text using a small number of support instances. This task enhances the model's adaptability and generalization capabilities in new domains and low-resource scenarios by reducing the need for annotated data, making it highly valuable with broad application potential.