An AI development team is adapting a large, pre-trained language model for a specialized legal document summarization task. To avoid the high computational cost of retraining the entire model, they prepend a small set of newly initialized, trainable numerical vectors to the input of the model. These vectors are then optimized using gradient descent to improve the model's performance on the summarization task, while the original parameters of the large model remain frozen. Which of the following statements best analyzes the core principle of the adaptation technique described?

You are tasked with adapting a large, pre-trained language model to a new task by optimizing a set of continuous, trainable vectors that are prepended to the input. The original model's parameters are to remain unchanged. Arrange the core steps of a single training iteration for this method in the correct sequence.

Evaluating LLM Adaptation Strategies