Applications of few-shot learning techniques. One application of few-shot learning techniques is in healthcare, where medical images with their diagnoses can be used to develop a classification model.

Natural language processing: In NLP tasks such as text classification, sentiment analysis, and named entity recognition, few-shot learning enables models to grasp the semantic understanding of ...

In-context learning is sometimes referred to as “few-shot learning.” Unlike task-specific fine-tuning, ICL does not require changing the model’s parameters, which makes it easier to use and ...