The process of using only the architecture of a pre-trained model and retraining it entirely with new data is known as _______ in transfer learning.

Fine-tuning in transfer learning involves taking a pre-trained model's architecture and training it with new data, adjusting the model's parameters to suit the specific task. It's a common technique for leveraging pre-trained models for custom tasks.