π Increase the quality of your RAG with a simple Linear Layer! No need to change your embedding model (keep that old OpenAI API).
Introducing EmbeddingAlign RAG, a novel approach to improve Retrieval-Augmented Generation (RAG) systems.
Key highlights: - Uses a simple linear transformation on existing embeddings - Boosts hit rate from 89% to 95% on real-world examples - Minor increase on latency (less than 10ms) - Works on top of blackbox embedding models (Mistral AI, OpenAI, Cohere,...) - No dataset needed (just your documents) - Train easily on CPU