In-Context Learning
A model performing a task from examples in the prompt, with no weight update.
Überblick
In-context learning is a model's ability to infer a task from examples supplied in the prompt and apply it to a new input, without any parameter change. It solves the problem that training a model per task is expensive when most tasks can be demonstrated in a paragraph. It exists because it emerged from scale rather than being designed: the capability appeared in large models that were never trained for it.
Technologiegraph
Wie In-Context Learning mit dem übrigen Stack zusammenhängt.
Werkzeuge
Software, die In-Context Learning implementiert oder integriert.