A research team develops a large language model by training it on a massive corpus of text from the internet. When they give the model the instruction, 'Translate the following English sentence to French,' the model instead continues the sentence in English with a grammatically correct but irrelevant phrase. However, after a second, much shorter training phase using a small, curated dataset of English-to-French sentence pairs, the model correctly performs the translation task. Which of the following statements best explains this change in the model's behavior?

Fine-Tuning as a Mechanism for Activating Pre-Trained Knowledge

Evaluating a Researcher's Conclusion on Model Training

The primary purpose of the supervisory phase that follows pre-training is to introduce entirely new capabilities, such as the ability to summarize text, which the model did not acquire in any form during its initial, large-scale training.