In-Context Learning

The ability of a large language model to adapt its behavior based on examples or instructions provided directly within the prompt, without any changes to its underlying weights. In-context learning is one of the most distinctive properties of modern language models, and an emergent behavior that appears above certain scales. The model learns what you want from context alone, not from training.
See also: few-shot learning, zero-shot learning, prompt engineering.