Beyond Benchmarks: Evaluating Embedding Model Similarity for Retrieval Augmented Generation Systems

Understand

The choice of embedding model is a crucial step in the design of Retrieval Augmented Generation (RAG) systems.

• Given the sheer volume of available options, identifying clusters of similar models streamlines this model selection process.
• Relying solely on benchmark performance scores only allows for a weak assessment of model similarity.
• Thus, in this study, we evaluate the similarity of embedding models within the context of RAG systems.