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 …

The multimodal task of Visual Question Answering (VQA) encompassing elements of
Computer Vision (CV) and Natural Language Processing (NLP), aims to generate answers …

Abstract The Visual Question Answering (VQA) task aspires to provide a meaningful testbed
for the development of AI models that can jointly reason over visual and natural language …

Multimodal LLMs are the natural evolution of LLMs and enlarge their capabilities so as to
work beyond the pure textual modality. As research is being carried out to design novel …

Outside-knowledge visual question answering (OK-VQA) requires the agent to comprehend
the image, make use of relevant knowledge from the entire web, and digest all the …

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 …

We propose Encyclopedic-VQA, a large scale visual question answering (VQA) dataset
featuring visual questions about detailed properties of fine-grained categories and …

The emergence of multimodal large models (MLMs) has significantly advanced the field of
visual understanding, offering remarkable capabilities in the realm of visual question …

Knowledge-based visual question answering (VQA) requires answering questions with
external knowledge in addition to the content of images. One dataset that is mostly used in …

Visual question answering (VQA) often requires an understanding of visual concepts and
language semantics, which relies on external knowledge. Most existing methods exploit pre …