Transformer and its variants have become the preferred option for multimodal vision-
language paradigms. However, they struggle with tasks that demand high-dependency …

Multimodal Artificial Intelligence (Multimodal AI), in general, involves various types of data
(eg, images, texts, or data collected from different sensors), feature engineering (eg …

With the rapid growth of Internet data traffic, the means of malicious attack become more
diversified. The single modal intrusion detection model cannot fully exploit the rich feature …

The emergence of the Transformer optimizes the interactive modeling of multimodal
information in visual question answering (VQA) tasks, helping machines better understand …

With the penetration of deep learning technology into forecasting and decision support
systems, enterprises have an increasingly urgent need for accurate forecasting of time …

Visual Question Answering (VQA) is a multimodal task that uses natural language to ask and
answer questions based on image content. For multimodal tasks, obtaining accurate …

Lane detection is a fundamental component of advanced driver assistance systems,
facilitating critical functionalities like Lane Keep/Change Assistance, Lane Departure …

Visual relationship modeling plays an indispensable role in visual question answering
(VQA). VQA models need to fully understand the visual scene and positional relationships …

The Transformer-based architecture, with its efficient parallel computation, long-range
dependency modeling, and context-aware capabilities, has showcased remarkable …

Due to its capacity to capture subgraph information within graph data, subgraph
representation learning has garnered considerable attention in recent years. However …