| name | 0.3.3-understand-mmr002 |
| description | ["0.3.3"] |
| Multi-modal embedding model | neural network architecture that projects content from different modalities into |
understand-mmr002
CALL NUMBER: deep_retrieval_augmented_.mmr002
DEFINITION: Multi-modal embedding model: neural network architecture that projects content from different modalities into a shared vector space enabling cross-modal similarity search.
Invoke this skill to understand mmr002 down to its primitives. The RELATIVE ROOT below is the least-fixed-point closure of everything it bundles from — the full import cone, grouped by the lib each prim comes from. Projected from a prover-typed KB (MAP/SWI-Prolog consistency gate): every reference below resolves.
THE RELATIVE ROOT (the import cone, by lib)
from deep_retrieval_augmented_
- mmr012 (d1): Cross-modal similarity metric: distance or similarity measure applicable across modality boundaries — enabling comparison of text query vectors against image embeddings, for example.
CONSUMERS (what needs this)
mmr003, mmr004, mmr009, mmr010, mmr024
Projected from the retrieval augmented generation architecture patterns KB (207 concepts / 225 relations) — consistency-typed by MAP; the facet list after the colon IS the cross-lib dependency web.
(leaf — this is an actual skill.)
