Definition
An advanced retrieval-augmented generation framework that enables an agent to query, retrieve, and synthesize information from disparate data types—such as text, images, video, and audio—into a unified generative response. It relies on shared embedding spaces or late-interaction models to align semantic meaning across different modalities for comprehensive context retrieval.
Extends beyond text-only retrieval to include non-textual data sources like diagrams, screenshots, or recordings.
"A museum curator who retrieves a historical scroll, a painted portrait, and a phonograph recording to provide a single, holistic answer to a visitor's question."
- Cross-Modal Embedding(Prerequisite)
- Vision-Language Models (VLM)(Component)
- Late Interaction(Optimization Technique)
- Vector Database(Infrastructure)
Conceptual Overview
An advanced retrieval-augmented generation framework that enables an agent to query, retrieve, and synthesize information from disparate data types—such as text, images, video, and audio—into a unified generative response. It relies on shared embedding spaces or late-interaction models to align semantic meaning across different modalities for comprehensive context retrieval.
Disambiguation
Extends beyond text-only retrieval to include non-textual data sources like diagrams, screenshots, or recordings.
Visual Analog
A museum curator who retrieves a historical scroll, a painted portrait, and a phonograph recording to provide a single, holistic answer to a visitor's question.