Definition
In-context learning (ICL) is a method utilizing pre-trained model to solve new tasks without fine-tuning by showing a few examples of the desire task to the model, allowing the model to infer the pattern and apply it to new instances. Unlike traditional machine learning, ICL doesn’t involve updating the model’s parameters. The model uses its existing knowledge to interpret and apply the new information.