Related papers: Knowledge Graph-Based approach for Sustainable 6G …
Knowledge graphs are inherently incomplete. Therefore substantial research has been directed toward knowledge graph completion (KGC), i.e., predicting missing triples from the information represented in the knowledge graph (KG). KG…
Knowledge graph (KG) completion aims to identify additional facts that can be inferred from the existing facts in the KG. Recent developments in this field have explored this task in the inductive setting, where at test time one sees…
Knowledge Graphs (KGs) are a powerful representation of linked data, offering flexibility, semantic richness, and support for knowledge enrichment and reasoning. They help data owners organize and exploit heterogeneous data to provide…
Knowledge Graph embedding provides a versatile technique for representing knowledge. These techniques can be used in a variety of applications such as completion of knowledge graph to predict missing information, recommender systems,…
Mobile communications have been undergoing a generational change every ten years. Whilst we are just beginning to roll out 5G networks, significant efforts are planned to standardize 6G that is expected to be commercially introduced by…
End-to-end (E2E) learning has recently been proposed to jointly design the modulator and symbol detector by using deep neural networks (DNNs). However, existing schemes lack sufficient capability to cancel multi-user interference (MUI) in…
The research community has already identified that, by 2030, 5G networks will reach the capacity limits, and hence, will be inadequate to support next generation bandwidth-hungry, ubiquitous, intelligent services, and applications.…
Incorporating Knowledge Graphs (KG) into recommeder system has attracted considerable attention. Recently, the technical trend of Knowledge-aware Recommendation (KGR) is to develop end-to-end models based on graph neural networks (GNNs).…
The convergence of robotics and next-generation communication is a critical driver of technological advancement. As the world transitions from 5G to 6G, the foundational capabilities of wireless networks are evolving to support increasingly…
The cellular network standard is gradually stepping towards the 6th Generation (6G). In 6G, the pioneering and exclusive features, such as creating connectivity even in space and under water, are attracting Governments, organizations and…
Device-to-Device (D2D) communication is a promising solution to meet the growing demands of 5G and future 6G networks by enabling direct communication between user devices. It enhances spectral efficiency (SE) and energy efficiency (EE),…
Modern GUI agents typically rely on a model-centric and step-wise interaction paradigm, where LLMs must re-interpret the UI and re-decide actions at every screen, which is fragile in long-horizon tasks. In this paper, we propose Executable…
The mobile communication system has transformed to be the fundamental infrastructure to support digital demands from all industry sectors, and 6G is envisioned to go far beyond the communication-only purpose. There is coming to a consensus…
The effective analysis of high-dimensional Electronic Health Record (EHR) data, with substantial potential for healthcare research, presents notable methodological challenges. Employing predictive modeling guided by a knowledge graph (KG),…
Knowledge graphs (KGs) have been increasingly employed for link prediction and recommendation using real-world datasets. However, the majority of current methods rely on static data, neglecting the dynamic nature and the hidden…
Smart services based on Internet of everything (IoE) are prophesied to reap notable attention by both academia and industry in the future. Although fifth-generation (5G) is a promising communication technology, however it cannot fulfill…
The recent upsurge of diversified mobile applications, especially those supported by Artificial Intelligence (AI), is spurring heated discussions on the future evolution of wireless communications. While 5G is being deployed around the…
The sixth generation (6G) mobile communication networks are expected to intelligently integrate into various aspects of modern digital society, including smart cities, homes, health-care, transportation, and factories. While offering a…
Knowledge-intensive tasks pose a significant challenge for Machine Learning (ML) techniques. Commonly adopted methods, such as Large Language Models (LLMs), often exhibit limitations when applied to such tasks. Nevertheless, there have been…
Knowledge graphs (KGs) are becoming essential resources for many downstream applications. However, their incompleteness may limit their potential. Thus, continuous curation is needed to mitigate this problem. One of the strategies to…