We present LLaVA-OneVision, a family of open large multimodal models (LMMs) developed
by consolidating our insights into data, models, and visual representations in the LLaVA …

In an era defined by the explosive growth of data and rapid technological advancements,
Multimodal Large Language Models (MLLMs) stand at the forefront of artificial intelligence …

We introduce Cambrian-1, a family of multimodal LLMs (MLLMs) designed with a vision-
centric approach. While stronger language models can enhance multimodal capabilities, the …

The recent surge of Multimodal Large Language Models (MLLMs) has fundamentally
reshaped the landscape of AI research and industry, shedding light on a promising path …

Visual instruction tuning has made considerable strides in enhancing the capabilities of
Large Multimodal Models (LMMs). However, existing open LMMs largely focus on single …

Since the emergence of ChatGPT, research on large language models (LLMs) has actively
progressed across various fields. LLMs, pre-trained on vast text datasets, have exhibited …

Abstract Recent advancements in Multimodal Large Language Models (LLMs) have focused
primarily on scaling by increasing text-image pair data and enhancing LLMs to improve …

Multi-modal Large Language Models (MLLMs) have demonstrated remarkable capabilities
in executing instructions for a variety of single-image tasks. Despite this progress, significant …

Visual data comes in various forms, ranging from small icons of just a few pixels to long
videos spanning hours. Existing multi-modal LLMs usually standardize these diverse visual …

The recent years have witnessed great advances in video generation. However, the
development of automatic video metrics is lagging significantly behind. None of the existing …