Related papers: Towards deployment-centric multimodal AI beyond vi…

The recent surge in artificial intelligence, particularly in multimodal processing technology, has advanced human-computer interaction, by altering how intelligent systems perceive, understand, and respond to contextual information (i.e.,…

AI is the workhorse of modern data analytics and omnipresent across many sectors. Large Language Models and multi-modal foundation models are today capable of generating code, charts, visualizations, etc. How will these massive developments…

Real-world problems are often dependent on multiple data modalities, making multimodal fusion essential for leveraging diverse information sources. In high-stakes domains, such as in healthcare, understanding how each modality contributes…

The rapid development of artificial intelligence has constantly reshaped the field of intelligent healthcare and medicine. As a vital technology, multimodal learning has increasingly garnered interest due to data complementarity,…

AI is being increasingly used to aid response efforts to humanitarian emergencies at multiple levels of decision-making. Such AI systems are generally understood to be stand-alone tools for decision support, with ethical assessments,…

This manuscript explores multimodal alignment, translation, fusion, and transference to enhance machine understanding of complex inputs. We organize the work into five chapters, each addressing unique challenges in multimodal machine…

Multimodal learning enhances the perceptual capabilities of cognitive systems by integrating information from different sensory modalities. However, existing multimodal fusion research typically assumes static integration, not fully…

The fundamental goal of artificial intelligence (AI) is to mimic the core cognitive activities of human. Despite tremendous success in the AI research, most of existing methods have only single-cognitive ability. To overcome this limitation…

Artificial intelligence (AI) plays a crucial role in autonomous driving (AD) research, propelling its development towards intelligence and efficiency. Currently, the development of AD technology follows two main technical paths:…

Computer-assisted diagnostic and prognostic systems of the future should be capable of simultaneously processing multimodal data. Multimodal deep learning (MDL), which involves the integration of multiple sources of data, such as images and…

Localization is a key requirement for mobile robot autonomy and human-robot interaction. Vision-based localization is accurate and flexible, however, it incurs a high computational burden which limits its application on many…

The integration of Large Language Models (LLMs) into medical applications has sparked widespread interest across the healthcare industry, from drug discovery and development to clinical decision support, assisting telemedicine, medical…

Large language models (LLMs) have achieved superior performance in powering text-based AI agents, endowing them with decision-making and reasoning abilities akin to humans. Concurrently, there is an emerging research trend focused on…

With the surge in the development of large language models, embodied intelligence has attracted increasing attention. Nevertheless, prior works on embodied intelligence typically encode scene or historical memory in an unimodal manner,…

Recent developments in artificial intelligence (AI) have permeated through an array of different immersive environments, including virtual, augmented, and mixed realities. AI brings a wealth of potential that centers on its ability to…

To facilitate the widespread acceptance of AI systems guiding decision-making in real-world applications, it is key that solutions comprise trustworthy, integrated human-AI systems. Not only in safety-critical applications such as…

A smart city can be seen as a framework, comprised of Information and Communication Technologies (ICT). An intelligent network of connected devices that collect data with their sensors and transmit them using cloud technologies in order to…

The paper tries to point out the benefits that can be derived from research advances in the implementation of concepts such as ambient intelligence (AmI) and ubiquitous or pervasive computing for promoting Universal Access (UA) to the…

Advances in Artificial Intelligence (AI) are helping tackle a growing number of societal challenges, demonstrating technology's increasing capability to address complex issues, including those outlined in the United Nations (UN) Sustainable…

The emergence of large language models (LLMs) has revolutionized AI development, yet the resource demands beyond a single cluster or even datacenter, limiting accessibility to well-resourced organizations. Decentralized training has emerged…