A vision encoder is a necessary component for allowing many leading LLMs to be able to work with images uploaded by users.

LLaVA 1.5 improves upon the original by connecting the language model and vision encoder through a multi-layer perceptron (MLP), a simple deep learning model where all neurons are fully connected.

The vision encoder processing in Gemma 3 uses bidirectional attention with image inputs. Bidirectional attention is a good approach for understanding tasks (as opposed to prediction tasks) ...

It employs a vision transformer encoder alongside a large language model (LLM). The vision encoder converts images into tokens, which an attention-based extractor then aligns with the LLM.

Gemma 3 packs an upgraded vision encoder that handles high-res and non-square images with ease. It also includes the ShieldGemma 2 image safety classifier, ...

“LLaVA represents a novel end-to-end trained large multimodal model that combines a vision encoder and Vicuna for general-purpose visual and language understanding, achieving impressive chat ...

Vision Language Models are a rapidly emerging class of multimodal AI models expanding in importance in the automotive world. Market leader NVIDIA has a concise definition of VLMs: Vision Language ...