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 …

Misinformation such as fake news and rumors is a serious threat on information ecosystems
and public trust. The emergence of Large Language Models (LLMs) has great potential to …

Language is essentially a complex, intricate system of human expressions governed by
grammatical rules. It poses a significant challenge to develop capable AI algorithms for …

Visual language models (VLMs) rapidly progressed with the recent success of large
language models. There have been growing efforts on visual instruction tuning to extend the …

In the realm of large multi-modal models (LMMs), efficient modality alignment is crucial yet
often constrained by the scarcity of high-quality image-text data. To address this bottleneck …

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 …

Abstract Large Vision-Language Models (LVLMs) have advanced considerably intertwining
visual recognition and language understanding to generate content that is not only coherent …

Retrieval-Augmented Generation (RAG) is a promising approach for mitigating the
hallucination of large language models (LLMs). However, existing research lacks rigorous …

As a primary means of information acquisition, information retrieval (IR) systems, such as
search engines, have integrated themselves into our daily lives. These systems also serve …

Abstract The eighth AI City Challenge highlighted the convergence of computer vision and
artificial intelligence in areas like retail warehouse settings and Intelligent Traffic Systems …