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 …

Benefiting from instrumental global dependency modeling of self-attention (SA), transformer-
based approaches have become the pivotal choices for numerous downstream visual …

We present a Recipe for Effective and Efficient zero-shot video-text Retrieval, dubbed M2-
RAAP. Upon popular image-text models like CLIP, most current adaptation-based video-text …

Abstract Knowledge-based visual reasoning requires the ability to associate outside
knowledge that is not present in a given image for cross-modal visual understanding. Two …

Fact-based Visual Question Answering (F-VQA) aims to answer questions with observed
images and external facts. The existing deep learning-based F-VQA methods still struggle to …

Objectives: Multimodal deep learning, incorporating images, text, videos, speech, and
acoustic signals, has grown significantly. This article aims to explore the untapped …

Abstract In Visual Question Answering (VQA) task, extracting semantic information from
multimodalities and effectively utilizing this information for interaction is crucial. Existing VQA …

Question answering methods are well-known for leveraging data bias, such as the language
prior in visual question answering and the position bias in machine reading comprehension …

More and more studies are looking at the use of dynamic off-chain transportation in IoT
systems that are based on payment channel networks (PCNs). Flexible routing in PCN …