Glossary
Model Parameters
Model parameters are the learned numerical values inside a language model that shape how it predicts tokens. They are adjusted during training or fine-tuning, not by a normal web search or page visit, and should not be confused with the external documents supplied during retrieval.
In plain terms
They are the learned internal settings that make the model behave as it does.
Why it matters
Parameters explain why model knowledge and retrieved web evidence are separate sources of information in an AI answer.
How to apply it
- Do not promise that publishing a page changes public model parameters.
- Use retrieval evidence for current claims.
- Distinguish model updates from search-index updates.
Example
A product fact can enter an answer through a retrieved page even though none of the model’s parameters changed.
Sources
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