What Is Few-Shot Learning? Definition, Examples & Patterns

Few-Shot Learning

Few-shot learning is a prompting technique where a small number of examples are included in the prompt to guide the model's behavior on a specific task. It can improve consistency but also introduces governance considerations around example selection and bias.

§01 / QUESTIONSterm: Few-Shot Learning

Questions

Common questions.

What is Few-Shot Learning?

Few-shot learning is a prompting technique where a small number of examples are included in the prompt to guide the model's behavior on a specific task.

How does Few-Shot Learning work?

It can improve consistency but also introduces governance considerations around example selection and bias.

Which terms are related to Few-Shot Learning?

Closely related concepts include Model Factsheet, Foundation Model, System Prompt, Training Data Poisoning. Each is defined in the Prefactor glossary.

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Few-Shot Learning

Common questions.

Where this fits.

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