In the past year, MultiModal Large Language Models (MM-LLMs) have undergone
substantial advancements, augmenting off-the-shelf LLMs to support MM inputs or outputs …

Recent development of Large Vision-Language Models (LVLMs) has attracted growing
attention within the AI landscape for its practical implementation potential. However,`` …

In this work, we discuss building performant Multimodal Large Language Models (MLLMs).
In particular, we study the importance of various architecture components and data choices …

Large language models (LLMs), exemplified by ChatGPT, have gained considerable
attention for their excellent natural language processing capabilities. Nonetheless, these …

Large language models (LLMs) have gained considerable attention for their excellent
natural language processing capabilities. Nonetheless, these LLMs present many …

In this paper, we introduce LLaVA-φ (LLaVA-Phi), an efficient multi-modal assistant that
harnesses the power of the recently advanced small language model, Phi-2, to facilitate …

Large Language Models (LLMs) have drawn a lot of attention due to their strong
performance on a wide range of natural language tasks, since the release of ChatGPT in …

We present MM-Navigator, a GPT-4V-based agent for the smartphone graphical user
interface (GUI) navigation task. MM-Navigator can interact with a smartphone screen as …

We present MobileVLM, a competent multimodal vision language model (MMVLM) targeted
to run on mobile devices. It is an amalgamation of a myriad of architectural designs and …

Current universal segmentation methods demonstrate strong capabilities in pixel-level
image and video understanding. However, they lack reasoning abilities and cannot be …