48 citations · 144 across the 27 of their papers we have counts for
27 papers
Skillsets on the Chain: A Blockchain-based Zero-Trust Framework for Agentic AI Networking
Yayu Gao, Yong Xiao, Hao Hu +5
Agentic AI networking (AgentNet) systems rely heavily on third-party skillset implementations and distributed multi-agent collaboration, yet they face major claim-to-capability inc…
Implicit Semantic-Aware Communication Based on Hypergraph Reasoning
Yiwei Liao, Shurui Tu, Yong Xiao +2
Semantic-aware communication has emerged as a transformative paradigm for next-generation communication systems, shifting the fundamental goal from transmitting bit-level symbols t…
SANet: A Semantic-aware Agentic AI Networking Framework for Cross-layer Optimization in 6G
Yong Xiao, Xubo Li, Haoran Zhou +5
Agentic AI networking (AgentNet) is a novel AI-native networking paradigm in which a large number of specialized AI agents collaborate to perform autonomous decision-making, dynami…
Implicit Semantic Communication Based on Bayesian Reconstruction Framework
Yiwei Liao, Shurui Tu, Yujie Zhou +3
Semantic communication is a novel communication paradigm that focuses on the transportation and delivery of the \emph{meaning} of messages. Recent results have verified that a grap…
Variable-Length Joint Source-Channel Coding for Semantic Communication
Yujie Zhou, Rulong Wang, Yong Xiao +2
This paper investigates a key challenge faced by joint source-channel coding (JSCC) in digital semantic communication (SemCom): the incompatibility between existing JSCC schemes th…
Distributed Information Bottleneck Theory for Multi-Modal Task-Aware Semantic Communication
Yujie Zhou, Cheng Peng, Rulong Wang +4
Semantic communication shifts the focus from bit-level accuracy to task-relevant semantic delivery, enabling efficient and intelligent communication for next-generation networks. H…
Robust Federated Learning against Model Perturbation in Edge Networks
Dongzi Jin, Yong Xiao, Yingyu Li
Federated Learning (FL) is a promising paradigm for realizing edge intelligence, allowing collaborative learning among distributed edge devices by sharing models instead of raw dat…
SANSee: A Physical-layer Semantic-aware Networking Framework for Distributed Wireless Sensing
Huixiang Zhu, Yong Xiao, Yingyu Li +2
Contactless device-free wireless sensing has recently attracted significant interest due to its potential to support a wide range of immersive human-machine interactive application…
Towards Net-Zero Carbon Emissions in Network AI for 6G and Beyond
Peng Zhang, Yong Xiao, Yingyu Li +3
A global effort has been initiated to reduce the worldwide greenhouse gas (GHG) emissions, primarily carbon emissions, by half by 2030 and reach net-zero by 2050. The development o…
Physical-Layer Semantic-Aware Network for Zero-Shot Wireless Sensing
Huixiang Zhu, Yong Xiao, Yingyu Li +2
Device-free wireless sensing has recently attracted significant interest due to its potential to support a wide range of immersive human-machine interactive applications. However,…
Reasoning over the Air: A Reasoning-based Implicit Semantic-Aware Communication Framework
Yong Xiao, Yiwei Liao, Yingyu Li +5
Semantic-aware communication is a novel paradigm that draws inspiration from human communication focusing on the delivery of the meaning of messages. It has attracted significant i…
Distributed Traffic Synthesis and Classification in Edge Networks: A Federated Self-supervised Learning Approach
Yong Xiao, Rong Xia, Yingyu Li +5
With the rising demand for wireless services and increased awareness of the need for data protection, existing network traffic analysis and management architectures are facing unpr…
Adversarial Learning for Implicit Semantic-Aware Communications
Zhimin Lu, Yong Xiao, Zijian Sun +5
Semantic communication is a novel communication paradigm that focuses on recognizing and delivering the desired meaning of messages to the destination users. Most existing works in…
Time-sensitive Learning for Heterogeneous Federated Edge Intelligence
Yong Xiao, Xiaohan Zhang, Guangming Shi +3
Real-time machine learning has recently attracted significant interest due to its potential to support instantaneous learning, adaptation, and decision making in a wide range of ap…
Life-long Learning for Reasoning-based Semantic Communication
Jingming Liang, Yong Xiao, Yingyu Li +2
Semantic communication is an emerging paradigm that focuses on understanding and delivering semantics, or meaning of messages. Most existing semantic communication solutions define…
Reasoning on the Air: An Implicit Semantic Communication Architecture
Yong Xiao, Yingyu Li, Guangming Shi +1
Semantic communication is a novel communication paradigm which draws inspiration from human communication focusing on the delivery of the meaning of a message to the intended users…
Rate-Distortion Theory for Strategic Semantic Communication
Yong Xiao, Xu Zhang, Yingyu Li +2
This paper analyzes the fundamental limit of the strategic semantic communication problem in which a transmitter obtains a limited number of indirect observation of an intrinsic se…
Optimizing Intelligent Reflecting Surface-Base Station Association for Mobile Networks
Dongzi Jin, Yong Xiao, Yingyu Li +2
This paper studies a multi-Intelligent Reflecting Surfaces (IRSs)-assisted wireless network consisting of multiple base stations (BSs) serving a set of mobile users. We focus on th…
Federated Traffic Synthesizing and Classification Using Generative Adversarial Networks
Chenxin Xu, Rong Xia, Yong Xiao +3
With the fast growing demand on new services and applications as well as the increasing awareness of data protection, traditional centralized traffic classification approaches are…
Spatio-temporal Modeling for Large-scale Vehicular Networks Using Graph Convolutional Networks
Juntong Liu, Yong Xiao, Yingyu Li +3
The effective deployment of connected vehicular networks is contingent upon maintaining a desired performance across spatial and temporal domains. In this paper, a graph-based fram…
From Semantic Communication to Semantic-aware Networking: Model, Architecture, and Open Problems
Guangming Shi, Yong Xiao, Yingyu Li +1
Existing communication systems are mainly built based on Shannon's information theory which deliberately ignores the semantic aspects of communication. The recent iteration of wire…
Optimizing Resource-Efficiency for Federated Edge Intelligence in IoT Networks
Yong Xiao, Yingyu Li, Guangming Shi +1
This paper studies an edge intelligence-based IoT network in which a set of edge servers learn a shared model using federated learning (FL) based on the datasets uploaded from a mu…
Towards Self-learning Edge Intelligence in 6G
Yong Xiao, Guangming Shi, Yingyu Li +2
Edge intelligence, also called edge-native artificial intelligence (AI), is an emerging technological framework focusing on seamless integration of AI, communication networks, and…
A Generative Learning Approach for Spatio-temporal Modeling in Connected Vehicular Network
Rong Xia, Yong Xiao, Yingyu Li +2
Spatio-temporal modeling of wireless access latency is of great importance for connected-vehicular systems. The quality of the molded results rely heavily on the number and quality…