A technique where a model learns to perform a task from a small number of examples provided in the prompt, without updating its parameters.
When you show the AI just a couple of examples and it figures out the pattern — like learning a game after watching someone play twice.
Teaching AI to do a new task by giving it just a few examples in the prompt, instead of retraining it on thousands of examples.
A technique where a model learns to perform a task from a small number of examples provided in the prompt, without updating its parameters.
In-context learning from k demonstration examples prepended to the input, enabling task adaptation without gradient updates — a key emergent capability of large language models.
Prompting with k exemplar input-output pairs that define a task distribution, leveraging the model's implicit Bayesian inference over latent task variables — performance scaling logarithmically with k and model size.
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