Moreover, task-specific fine-tuning of embedding models
is essential to ensure that the model comprehends the user
query in terms of content relevance. A model without fine-
tuning may not adequately address the requirements of a spe-
cific task. Consequently, fine-tuning an embedding model be-
comes crucial for downstream applications. There are two
primary paradigms in embedding fine-tuning methods.
RAG forLargeLanguageModels-ASurvey