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In-Context Learning

1 min read

What It Means

The ability of LLMs to learn from examples provided in the prompt without updating model weights.

In-context learning (ICL) enables rapid adaptation through few-shot examples, a key capability for versatile agents.

How It Works

  • Examples provided in prompt
  • Model infers pattern
  • Applies to new inputs
  • No training required

Limitations

  • Context window constraints
  • Not persistent
  • Variable reliability
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