AI / LLM Basics Interview Questions
Define Few-Shot Learning?
Few-shot learning is when a handful of example input-output pairs are included directly in the prompt to demonstrate exactly what kind of response is wanted, before asking the model to handle a new case.
- Typically uses somewhere between two and a handful of examples
- Helps the model understand a specific format, tone, or task structure that a plain instruction alone might leave ambiguous
- Consumes more of the context window than zero-shot prompting, since the examples themselves take up tokens
Few-shot prompting is a practical, no-training-required way to steer a model toward a very specific style of response when a plain instruction isn't precise enough on its own.
What is included directly in the prompt for few-shot learning?
Does few-shot prompting require retraining the model?
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