Connecting text and visual modalities plays an essential role in generative intelligence. For
this reason, inspired by the success of large language models, significant research efforts …

In this work, we propose a training-free method to inject visual prompts into Multimodal
Large Language Models (MLLMs) through learnable latent variable optimization. We …

Though advanced in understanding visual information with human languages, Large Vision-
Language Models (LVLMs) still suffer from multimodal hallucinations. A natural concern is …

Videos carry rich visual information including object description, action, interaction, etc., but
the existing multimodal large language models (MLLMs) fell short in referential …

Video Large Language Models (Video LLMs) have recently exhibited remarkable
capabilities in general video understanding. However, they mainly focus on holistic …

Aligning vision and language concepts at a finer level remains an essential topic of
multimodal large language models (MLLMs), particularly for tasks such as referring and …

We present Omni-RGPT, a multimodal large language model designed to facilitate region-
level comprehension for both images and videos. To achieve consistent region …

The personalization model has gained significant attention in image generation yet remains
underexplored for large vision-language models (LVLMs). Beyond generic ones, with …

Visual-language models (VLM) have emerged as a powerful tool for learning a unified
embedding space for vision and language. Inspired by large language models, which have …

Spatial Reasoning is an important component of human cognition and is an area in which
the latest Vision-language models (VLMs) show signs of difficulty. The current analysis …