Philippe Bouzaglou

Vector search inevitably involves representing the documents or items via embeddings at indexing time. In most cases, these embeddings remain frozen and contain strictly the information that the embedding model was able to deduct from the inputs.

Modern search systems return both text and images, requiring evaluation beyond traditional keyword matching. Our approach leverages embedding models to assess search quality across all modalities simultaneously.