Definition
The process of adapting a pre-trained large language model to a specific domain or task by training it on additional domain-specific data. Fine-tuning allows organizations to customize model behavior without retraining from scratch.
Why it matters
Fine-tuning is how organizations embed proprietary logic into models, but poisoned training data or compromise during fine-tuning can inject backdoors or unintended behaviors that are difficult to detect.