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 …

The Large Vision-Language Model (LVLM) has enhanced the performance of various
downstream tasks in visual-language understanding. Most existing approaches encode …

Efficient fine-tuning is vital for adapting large language models (LLMs) to downstream tasks.
However, it requires non-trivial efforts to implement these methods on different models. We …

We introduce InternVideo2, a new family of video foundation models (ViFM) that achieve the
state-of-the-art results in video recognition, video-text tasks, and video-centric dialogue. Our …

The exponential growth of large language models (LLMs) has opened up numerous
possibilities for multi-modal AGI systems. However the progress in vision and vision …

Large language models have demonstrated impressive universal capabilities across a wide
range of open-ended tasks and have extended their utility to encompass multimodal …

With the advent and widespread deployment of Multimodal Large Language Models
(MLLMs), the imperative to ensure their safety has become increasingly pronounced …

With the burgeoning growth of online video platforms and the escalating volume of video
content, the demand for proficient video understanding tools has intensified markedly. Given …

World models are progressively being employed across diverse fields, extending from basic
environment simulation to complex scenario construction. However, existing models are …

AI agents based on multimodal large language models (LLMs) are expected to revolutionize
human-computer interaction, and offer more personalized assistant services across various …