Multimodal LLMs contain an encoder, LLM, and a “connector” between the multiple modalities. The LLM is typically pre-trained. For instance, LLaVA uses the CLIP ViT-L/14 for an image encoder and Vicuna ...

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

The key to addressing these challenges lies in separating the encoder and decoder components of multimodal machine learning models. Modern multimodal models (for speech generation or visual ...

Llama 3.2 introduces a groundbreaking architecture that seamlessly integrates a pre-trained image encoder with a language ... a powerful and versatile multimodal LLM, Meta AI is helping to bridge ...

The paper was published last week and is titled “MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training ... ablations of the image encoder, the vision language connector, and ...

Three distinct architectures: NVLM 1.0 includes NVLM-D (decoder ... LLM backbone and vision encoder were kept frozen. This method preserved the text-only performance of the model while adding ...

Originally introduced in a 2017 paper, “Attention Is All You Need” from researchers at Google, the transformer was introduced as an encoder-decoder architecture specifically designed for ...

Most recently, the Centre announced the BharatGen project, touted as the world’s first government-funded multimodal large language model (LLM) project. The Ministry of Science said that it will ...