In-Context Learning
A model performing a task from examples in the prompt, with no weight update.
Resumen
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.
Grafo de tecnologías
Cómo se conecta In-Context Learning con el resto del stack.
Herramientas
Software que implementa o se integra con In-Context Learning.