Term tag: few-shot learning

Few-shot Learning (FSL)

Teaching a model a task by showing it a handful of worked examples. In its modern form, few-shot prompting, no weights are updated at all.

Meta-Learning

Learning to learn: training a model across thousands of tiny tasks so it adapts from a handful of examples — and how that differs from fine-tuning.