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A model's ability to learn a task from examples or instructions placed in the prompt at inference time, without any change to its weights.
In-context learning is the emergent behaviour Brown et al. (2020) observed in GPT-3: shown a few examples in the prompt, the model performs the task without gradient updates. The survey by Dong et al. (2022) catalogues how it works and what makes it reliable.
It is what makes prompting, few-shot examples and chain-of-thought effective — and why a single frozen model can do so many different jobs.
Primary, peer-reviewed and archival sources for this definition.
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