Hongyang Du
YOU?
Author Swipe
View article: JAUNT: Joint Alignment of User Intent and Network State for QoE-centric LLM Tool Routing
JAUNT: Joint Alignment of User Intent and Network State for QoE-centric LLM Tool Routing Open
Large Language Models (LLMs) increasingly rely on emerging protocols such as the Model Context Protocol (MCP) to invoke external tools and services. However, current tool routing mechanisms remain fragile because they only consider functio…
View article: NetMCP: Network-Aware Model Context Protocol Platform for LLM Capability Extension
NetMCP: Network-Aware Model Context Protocol Platform for LLM Capability Extension Open
Large Language Models (LLMs) remain static in functionality after training, and extending their capabilities requires integration with external data, computation, and services. The Model Context Protocol (MCP) has emerged as a standard int…
View article: Tumor necrosis-informed prognostic nomogram for clear cell renal cell carcinoma model development and clinical validation
Tumor necrosis-informed prognostic nomogram for clear cell renal cell carcinoma model development and clinical validation Open
View article: Optimizing Split Federated Learning with Unstable Client Participation
Optimizing Split Federated Learning with Unstable Client Participation Open
To enable training of large artificial intelligence (AI) models at the network edge, split federated learning (SFL) has emerged as a promising approach by distributing computation between edge devices and a server. However, while unstable …
View article: Explainable machine learning for predicting distant metastases in renal cell carcinoma patients: a population-based retrospective study
Explainable machine learning for predicting distant metastases in renal cell carcinoma patients: a population-based retrospective study Open
Background Distant metastasis is a key factor contributing to poor prognosis in renal cell carcinoma (RCC). Early prediction of metastasis is crucial for developing personalized treatment plans and improving patient outcomes. This study ai…
View article: Diffusion-Modeled Reinforcement Learning for Carbon and Risk-Aware Microgrid Optimization
Diffusion-Modeled Reinforcement Learning for Carbon and Risk-Aware Microgrid Optimization Open
This paper introduces DiffCarl, a diffusion-modeled carbon- and risk-aware reinforcement learning algorithm for intelligent operation of multi-microgrid systems. With the growing integration of renewables and increasing system complexity, …
View article: Energy-Efficient RSMA-enabled Low-altitude MEC Optimization Via Generative AI-enhanced Deep Reinforcement Learning
Energy-Efficient RSMA-enabled Low-altitude MEC Optimization Via Generative AI-enhanced Deep Reinforcement Learning Open
The growing demand for low-latency computing in 6G is driving the use of UAV-based low-altitude mobile edge computing (MEC) systems. However, limited spectrum often leads to severe uplink interference among ground terminals (GTs). In this …
View article: MAD-Spear: A Conformity-Driven Prompt Injection Attack on Multi-Agent Debate Systems
MAD-Spear: A Conformity-Driven Prompt Injection Attack on Multi-Agent Debate Systems Open
Multi-agent debate (MAD) systems leverage collaborative interactions among large language models (LLMs) agents to improve reasoning capabilities. While recent studies have focused on increasing the accuracy and scalability of MAD systems, …
View article: Graph Diffusion-Based AeBS Deployment and Resource Allocation for RSMA-Enabled URLLC Low-Altitude Economy Networks
Graph Diffusion-Based AeBS Deployment and Resource Allocation for RSMA-Enabled URLLC Low-Altitude Economy Networks Open
As a key component of low-altitude economic networks, aerial base stations (AeBSs) provide flexible and reliable wireless coverage to support 6G ultra-reliable and low-latency communication (URLLC) services. However, limited spectrum resou…
View article: Generative Semantic Communication: Architectures, Technologies, and Applications
Generative Semantic Communication: Architectures, Technologies, and Applications Open
View article: Empowering Intelligent Low-altitude Economy with Large AI Model Deployment
Empowering Intelligent Low-altitude Economy with Large AI Model Deployment Open
Low-altitude economy (LAE) represents an emerging economic paradigm that redefines commercial and social aerial activities. Large artificial intelligence models (LAIMs) offer transformative potential to further enhance the intelligence of …
View article: Chain-of-Thought for Large Language Model-empowered Wireless Communications
Chain-of-Thought for Large Language Model-empowered Wireless Communications Open
Recent advances in large language models (LLMs) have opened new possibilities for automated reasoning and decision-making in wireless networks. However, applying LLMs to wireless communications presents challenges such as limited capabilit…
View article: Temporal Spectrum Cartography in Low-Altitude Economy Networks: A Generative AI Framework with Multi-Agent Learning
Temporal Spectrum Cartography in Low-Altitude Economy Networks: A Generative AI Framework with Multi-Agent Learning Open
This paper introduces a two-stage generative AI (GenAI) framework tailored for temporal spectrum cartography in low-altitude economy networks (LAENets). LAENets, characterized by diverse aerial devices such as UAVs, rely heavily on wireles…
View article: VideoHallu: Evaluating and Mitigating Multi-modal Hallucinations for Synthetic Videos
VideoHallu: Evaluating and Mitigating Multi-modal Hallucinations for Synthetic Videos Open
Synthetic video generation using foundation models has gained significant attention due to its realism and broad applications. However, while these models excel at generating visually coherent and high-quality video frames, they often over…
View article: Model Context Protocol-based Internet of Experts For Wireless Environment-aware LLM Agents
Model Context Protocol-based Internet of Experts For Wireless Environment-aware LLM Agents Open
Large Language Models (LLMs) exhibit strong general-purpose reasoning abilities but lack access to wireless environment information due to the absence of native sensory input and domain-specific priors. Previous attempts to apply LLMs in w…
View article: Task-Oriented Semantic Communication in Large Multimodal Models-Based Vehicle Networks
Task-Oriented Semantic Communication in Large Multimodal Models-Based Vehicle Networks Open
Task-oriented semantic communication has emerged as a fundamental approach for enhancing performance in various communication scenarios. While recent advances in Generative Artificial Intelligence (GenAI), such as Large Language Models (LL…
View article: Supervised Score-Based Modeling by Gradient Boosting
Supervised Score-Based Modeling by Gradient Boosting Open
Score-based generative models can effectively learn the distribution of data by estimating the gradient of the distribution. Due to the multi-step denoising characteristic, researchers have recently considered combining score-based generat…
View article: Revolution of Wireless Signal Recognition for 6G: Recent Advances, Challenges and Future Directions
Revolution of Wireless Signal Recognition for 6G: Recent Advances, Challenges and Future Directions Open
Wireless signal recognition (WSR) is a crucial technique for intelligent communications and spectrum sharing in the next six-generation (6G) wireless communication networks. It can be utilized to enhance network performance and efficiency,…
View article: Relationship of obesity, body fat, benign adrenal tumors and the mediating mechanism: a two-step mendelian randomization study
Relationship of obesity, body fat, benign adrenal tumors and the mediating mechanism: a two-step mendelian randomization study Open
View article: Generative AI-enabled Wireless Communications for Robust Low-Altitude Economy Networking
Generative AI-enabled Wireless Communications for Robust Low-Altitude Economy Networking Open
Low-Altitude Economy Networks (LAENets) have emerged as significant enablers of social activities, offering low-altitude services such as the transportation of packages, groceries, and medical supplies. Owing to their control mechanisms an…
View article: Generative AI Enabled Robust Data Augmentation for Wireless Sensing in ISAC Networks
Generative AI Enabled Robust Data Augmentation for Wireless Sensing in ISAC Networks Open
Integrated sensing and communication (ISAC) uses the same software and hardware resources to achieve both communication and sensing functionalities. Thus, it stands as one of the core technologies of 6G and has garnered significant attenti…
View article: Intelligent Mobile AI-Generated Content Services via Interactive Prompt Engineering and Dynamic Service Provisioning
Intelligent Mobile AI-Generated Content Services via Interactive Prompt Engineering and Dynamic Service Provisioning Open
Due to massive computational demands of large generative models, AI-Generated Content (AIGC) can organize collaborative Mobile AIGC Service Providers (MASPs) at network edges to provide ubiquitous and customized content generation for reso…
View article: Multi-objective Low-altitude IRS-assisted ISAC Optimization via Generative AI-enhanced Deep Reinforcement Learning
Multi-objective Low-altitude IRS-assisted ISAC Optimization via Generative AI-enhanced Deep Reinforcement Learning Open
Integrated sensing and communication (ISAC) has garnered substantial research interest owing to its pivotal role in advancing the development of next-generation (6G) wireless networks. However, achieving a performance balance between commu…
View article: Contract-Inspired Contest Theory for Controllable Image Generation in Mobile Edge Metaverse
Contract-Inspired Contest Theory for Controllable Image Generation in Mobile Edge Metaverse Open
The rapid advancement of immersive technologies has propelled the development of the Metaverse, where the convergence of virtual and physical realities necessitates the generation of high-quality, photorealistic images to enhance user expe…
View article: Adaptive Contextual Caching for Mobile Edge Large Language Model Service
Adaptive Contextual Caching for Mobile Edge Large Language Model Service Open
Mobile edge Large Language Model (LLM) deployments face inherent constraints, such as limited computational resources and network bandwidth. Although Retrieval-Augmented Generation (RAG) mitigates some challenges by integrating external kn…
View article: Benchmark Evaluations, Applications, and Challenges of Large Vision Language Models: A Survey
Benchmark Evaluations, Applications, and Challenges of Large Vision Language Models: A Survey Open
Multimodal Vision Language Models (vlms) have emerged as a transformative technology at the intersection of computer vision and natural language processing, enabling machines to perceive and reason about the world through both visual and t…
View article: Online Collaborative Resource Allocation and Task Offloading for Multi-access Edge Computing
Online Collaborative Resource Allocation and Task Offloading for Multi-access Edge Computing Open
Multi-access edge computing (MEC) is emerging as a promising paradigm to provide flexible computing services close to user devices (UDs). However, meeting the computation-hungry and delay-sensitive demands of UDs faces several challenges, …
View article: Joint Optimization of UAV-Carried IRS for Urban Low Altitude mmWave Communications with Deep Reinforcement Learning
Joint Optimization of UAV-Carried IRS for Urban Low Altitude mmWave Communications with Deep Reinforcement Learning Open
Emerging technologies in sixth generation (6G) of wireless communications, such as terahertz communication and ultra-massive multiple-input multiple-output, present promising prospects. Despite the high data rate potential of millimeter wa…
View article: A Survey of State of the Art Large Vision Language Models: Alignment, Benchmark, Evaluations and Challenges
A Survey of State of the Art Large Vision Language Models: Alignment, Benchmark, Evaluations and Challenges Open
Multimodal Vision Language Models (VLMs) have emerged as a transformative topic at the intersection of computer vision and natural language processing, enabling machines to perceive and reason about the world through both visual and textua…
View article: Embodied AI-Enhanced Vehicular Networks: An Integrated Large Language Models and Reinforcement Learning Method
Embodied AI-Enhanced Vehicular Networks: An Integrated Large Language Models and Reinforcement Learning Method Open
This paper investigates adaptive transmission strategies in embodied AI-enhanced vehicular networks by integrating large language models (LLMs) for semantic information extraction and deep reinforcement learning (DRL) for decision-making. …