Knowledge Graphs (KGs) play a pivotal role in advancing various AI applications, with the
semantic web community's exploration into multi-modal dimensions unlocking new avenues …

Answering visual queries is a complex task that requires both visual processing and
reasoning. End-to-end models, the dominant approach for this task, do not explicitly …

We propose InternLM-XComposer, a vision-language large model that enables advanced
image-text comprehension and composition. The innovative nature of our model is …

This paper offers an insightful examination of how currently top-trending AI technologies, ie,
generative artificial intelligence (Generative AI) and large language models (LLMs), are …

In this paper, we propose an autonomous information seeking visual question answering
framework, AVIS. Our method leverages a Large Language Model (LLM) to dynamically …

As one of the most advanced techniques in AI, Retrieval-Augmented Generation (RAG) can
offer reliable and up-to-date external knowledge, providing huge convenience for numerous …

Pre-trained vision and language models have demonstrated state-of-the-art capabilities over
existing tasks involving images and texts, including visual question answering. However, it …

The development of Artificial Intelligence Generated Content (AIGC) has been facilitated by
advancements in model algorithms, scalable foundation model architectures, and the …

As Large Language Models (LLMs) become popular, there emerged an important trend of
using multimodality to augment the LLMs' generation ability, which enables LLMs to better …

Abstract Vision-Language Models (VLMs) are pretrained on large diverse and noisy web-
crawled datasets. This underscores the critical need for dataset pruning as the quality of …