Table 1: Comparison between RAG and Fine-Tuning

Feature Comparison

RAG

Fine-Tuning

Knowledge Updates

Directly updating the retrieval knowledge
base ensures that the information remains
current without the need for frequent retrain-
ing, making it well-suited for dynamic data
environments.

External Knowledge

Proficient in leveraging external resources,
particularly suitable for accessing documents
or other structured/unstructured databases.

Data Processing

Involves minimal data processing and han-
dling.

Stores static data, requiring retraining for
knowledge and data updates.

Can be utilized to align the externally ac-
quired knowledge from pretraining with large
language models, but may be less practical
for frequently changing data sources.

Depends on the creation of high-quality
datasets, and limited datasets may not result
in significant performance improvements.

Model Customization
RAG forLargeLanguageModels-ASurvey