Definition
The process of querying a vector store using high-dimensional embeddings—typically generated by contrastive models like CLIP—to retrieve images semantically relevant to a user prompt. In RAG, this involves a trade-off between the compute cost of high-dimensional visual encoders and the retrieval precision required for downstream multimodal LLMs.
Uses latent space similarity rather than traditional metadata or filename-based keyword searching.
"A digital color-matching station that finds a specific paint sample by scanning its chemical composition rather than looking up its brand name."
- Multimodal Embeddings(Prerequisite)
- Vector Database(Component)
- Cosine Similarity(Retrieval Metric)
- LMM (Large Multimodal Model)(Downstream Consumer)
Conceptual Overview
The process of querying a vector store using high-dimensional embeddings—typically generated by contrastive models like CLIP—to retrieve images semantically relevant to a user prompt. In RAG, this involves a trade-off between the compute cost of high-dimensional visual encoders and the retrieval precision required for downstream multimodal LLMs.
Disambiguation
Uses latent space similarity rather than traditional metadata or filename-based keyword searching.
Visual Analog
A digital color-matching station that finds a specific paint sample by scanning its chemical composition rather than looking up its brand name.