Few-Shot Learning

Entity Type: Glossary ID: few-shot-learning

Definition: A machine learning approach where models learn to perform tasks with only a few examples. In the context of language models, few-shot learning involves providing examples in the prompt to guide the model's behavior on new tasks.

Related Terms: - zero-shot-learning - in-context-learning - meta-learning - prompt-engineering

Source Urls: - https://en.wikipedia.org/wiki/Few-shot_learning

Tags: - learning-paradigms - prompting - transfer-learning

Status: active

Version: 1.0.0

Created At: 2025-08-31

Last Updated: 2025-08-31