Definition
Visual Question Answering (VQA) is a multimodal task where an AI agent or RAG system processes an image and a natural language query to generate a specific textual answer based on visual reasoning. In RAG architectures, it is increasingly used to interpret non-textual data—such as charts, diagrams, or UI screenshots—that cannot be captured by standard text-based embedding models.
Unlike image captioning which summarizes a scene, VQA requires targeted reasoning to answer specific queries about visual elements.
"A witness on a stand being asked to identify specific details from a photograph presented as evidence."
- Multimodal RAG(System Architecture)
- Optical Character Recognition (OCR)(Prerequisite/Alternative)
- Vision-Language Model (VLM)(Underlying Model Class)
- Image Embedding(Component)
Conceptual Overview
Visual Question Answering (VQA) is a multimodal task where an AI agent or RAG system processes an image and a natural language query to generate a specific textual answer based on visual reasoning. In RAG architectures, it is increasingly used to interpret non-textual data—such as charts, diagrams, or UI screenshots—that cannot be captured by standard text-based embedding models.
Disambiguation
Unlike image captioning which summarizes a scene, VQA requires targeted reasoning to answer specific queries about visual elements.
Visual Analog
A witness on a stand being asked to identify specific details from a photograph presented as evidence.