Vision-Language Model
A model that jointly understands and reasons about both visual and textual information.
Overview
Vision-language models (VLMs) are multimodal AI systems that can process, understand, and generate content involving both images and text. They can perform tasks like visual question answering, image captioning, visual reasoning, and document understanding by jointly processing visual and textual inputs.
Key Details
Architectures include CLIP-style dual encoders, Flamingo-style cross-attention models, and modern integrated approaches (GPT-4V, Claude 3, Gemini) that feed image tokens directly into a language model. VLMs enable powerful applications including document analysis, visual search, accessibility tools, autonomous systems, and GUI understanding. The trend is toward increasingly capable models that handle multiple images, video, and complex visual reasoning.