Search Results for author: Jiawen Kang

Found 66 papers, 8 papers with code

Exploring Attention-Aware Network Resource Allocation for Customized Metaverse Services

1 code implementation31 Jul 2022 Hongyang Du, Jiacheng Wang, Dusit Niyato, Jiawen Kang, Zehui Xiong, Xuemin, Shen, Dong In Kim

With the help of UOAL, we propose an attention-aware network resource allocation algorithm that has two steps, i. e., attention prediction and QoE maximization.

Attention-aware Resource Allocation and QoE Analysis for Metaverse xURLLC Services

2 code implementations10 Aug 2022 Hongyang Du, Jiazhen Liu, Dusit Niyato, Jiawen Kang, Zehui Xiong, Junshan Zhang, Dong In Kim

Although conventional ultra-reliable and low-latency communications (URLLC) can satisfy objective KPIs, it is difficult to provide a personalized immersive experience that is a distinctive feature of the Metaverse.

AI-Generated Incentive Mechanism and Full-Duplex Semantic Communications for Information Sharing

1 code implementation3 Mar 2023 Hongyang Du, Jiacheng Wang, Dusit Niyato, Jiawen Kang, Zehui Xiong, Dong In Kim

Specifically, a user can transmit the generated content and semantic information extracted from their view image to nearby users, who can then use this information to obtain the spatial matching of computation results under their view images.

Mixed Reality

Data Heterogeneity-Robust Federated Learning via Group Client Selection in Industrial IoT

1 code implementation3 Feb 2022 Zonghang Li, Yihong He, Hongfang Yu, Jiawen Kang, Xiaoping Li, Zenglin Xu, Dusit Niyato

In this paper, we propose FedGS, which is a hierarchical cloud-edge-end FL framework for 5G empowered industries, to improve industrial FL performance on non-i. i. d.

Federated Learning

Privacy-preserving Traffic Flow Prediction: A Federated Learning Approach

1 code implementation19 Mar 2020 Yi Liu, James J. Q. Yu, Jiawen Kang, Dusit Niyato, Shuyu Zhang

Through extensive case studies on a real-world dataset, it is shown that FedGRU's prediction accuracy is 90. 96% higher than the advanced deep learning models, which confirm that FedGRU can achieve accurate and timely traffic prediction without compromising the privacy and security of raw data.

Clustering Federated Learning +2

CN-CELEB: a challenging Chinese speaker recognition dataset

2 code implementations31 Oct 2019 Yue Fan, Jiawen Kang, Lantian Li, Kaicheng Li, Haolin Chen, Sitong Cheng, Pengyuan Zhang, Ziya Zhou, Yunqi Cai, Dong Wang

These datasets tend to deliver over optimistic performance and do not meet the request of research on speaker recognition in unconstrained conditions.

Speaker Recognition

Domain-Invariant Speaker Vector Projection by Model-Agnostic Meta-Learning

1 code implementation25 May 2020 Jiawen Kang, Ruiqi Liu, Lantian Li, Yunqi Cai, Dong Wang, Thomas Fang Zheng

Domain generalization remains a critical problem for speaker recognition, even with the state-of-the-art architectures based on deep neural nets.

Audio and Speech Processing

Incentive Design for Efficient Federated Learning in Mobile Networks: A Contract Theory Approach

no code implementations16 May 2019 Jiawen Kang, Zehui Xiong, Dusit Niyato, Han Yu, Ying-Chang Liang, Dong In Kim

To strengthen data privacy and security, federated learning as an emerging machine learning technique is proposed to enable large-scale nodes, e. g., mobile devices, to distributedly train and globally share models without revealing their local data.

Federated Learning

A Secure Federated Learning Framework for 5G Networks

no code implementations12 May 2020 Yi Liu, Jialiang Peng, Jiawen Kang, Abdullah M. Iliyasu, Dusit Niyato, Ahmed A. Abd El-Latif

In this article, we propose a blockchain-based secure FL framework to create smart contracts and prevent malicious or unreliable participants from involving in FL.

Federated Learning

Reliable Federated Learning for Mobile Networks

no code implementations14 Oct 2019 Jiawen Kang, Zehui Xiong, Dusit Niyato, Yuze Zou, Yang Zhang, Mohsen Guizani

Based on this metric, a reliable worker selection scheme is proposed for federated learning tasks.

Cryptography and Security

Federated Learning for 6G Communications: Challenges, Methods, and Future Directions

no code implementations4 Jun 2020 Yi Liu, Xingliang Yuan, Zehui Xiong, Jiawen Kang, Xiaofei Wang, Dusit Niyato

As the 5G communication networks are being widely deployed worldwide, both industry and academia have started to move beyond 5G and explore 6G communications.

Federated Learning

Towards Federated Learning in UAV-Enabled Internet of Vehicles: A Multi-Dimensional Contract-Matching Approach

no code implementations8 Apr 2020 Wei Yang Bryan Lim, Jianqiang Huang, Zehui Xiong, Jiawen Kang, Dusit Niyato, Xian-Sheng Hua, Cyril Leung, Chunyan Miao

Coupled with the rise of Deep Learning, the wealth of data and enhanced computation capabilities of Internet of Vehicles (IoV) components enable effective Artificial Intelligence (AI) based models to be built.

Signal Processing Networking and Internet Architecture

Deep Anomaly Detection for Time-series Data in Industrial IoT: A Communication-Efficient On-device Federated Learning Approach

no code implementations19 Jul 2020 Yi Liu, Sahil Garg, Jiangtian Nie, Yang Zhang, Zehui Xiong, Jiawen Kang, M. Shamim Hossain

Third, to adapt the proposed framework to the timeliness of industrial anomaly detection, we propose a gradient compression mechanism based on Top-\textit{k} selection to improve communication efficiency.

Anomaly Detection Federated Learning +2

Squeezing value of cross-domain labels: a decoupled scoring approach for speaker verification

no code implementations27 Oct 2020 Lantian Li, Yang Zhang, Jiawen Kang, Thomas Fang Zheng, Dong Wang

Domain mismatch often occurs in real applications and causes serious performance reduction on speaker verification systems.

Speaker Verification

Scalable and Communication-efficient Decentralized Federated Edge Learning with Multi-blockchain Framework

no code implementations10 Aug 2020 Jiawen Kang, Zehui Xiong, Chunxiao Jiang, Yi Liu, Song Guo, Yang Zhang, Dusit Niyato, Cyril Leung, Chunyan Miao

This framework can achieve scalable and flexible decentralized FEL by individually manage local model updates or model sharing records for performance isolation.

Cryptography and Security

Towards Communication-efficient and Attack-Resistant Federated Edge Learning for Industrial Internet of Things

no code implementations8 Dec 2020 Yi Liu, Ruihui Zhao, Jiawen Kang, Abdulsalam Yassine, Dusit Niyato, Jialiang Peng

Second, we propose an asynchronous local differential privacy mechanism, which improves communication efficiency and mitigates gradient leakage attacks by adding well-designed noise to the gradients of edge nodes.

Edge-computing

Robust Semi-supervised Federated Learning for Images Automatic Recognition in Internet of Drones

no code implementations3 Jan 2022 Zhe Zhang, Shiyao Ma, Zhaohui Yang, Zehui Xiong, Jiawen Kang, Yi Wu, Kejia Zhang, Dusit Niyato

This emerging technology relies on sharing ground truth labeled data between Unmanned Aerial Vehicle (UAV) swarms to train a high-quality automatic image recognition model.

Federated Learning Privacy Preserving

The CUHK-TENCENT speaker diarization system for the ICASSP 2022 multi-channel multi-party meeting transcription challenge

no code implementations4 Feb 2022 Naijun Zheng, Na Li, Xixin Wu, Lingwei Meng, Jiawen Kang, Haibin Wu, Chao Weng, Dan Su, Helen Meng

This paper describes our speaker diarization system submitted to the Multi-channel Multi-party Meeting Transcription (M2MeT) challenge, where Mandarin meeting data were recorded in multi-channel format for diarization and automatic speech recognition (ASR) tasks.

Action Detection Activity Detection +6

TalkTive: A Conversational Agent Using Backchannels to Engage Older Adults in Neurocognitive Disorders Screening

no code implementations16 Feb 2022 Zijian Ding, Jiawen Kang, Tinky Oi Ting HO, Ka Ho Wong, Helene H. Fung, Helen Meng, Xiaojuan Ma

This is used in the development of TalkTive, a CA which can predict both timing and form of backchanneling during cognitive assessments.

Reconfigurable Intelligent Surface-Aided Joint Radar and Covert Communications: Fundamentals, Optimization, and Challenges

no code implementations5 Mar 2022 Hongyang Du, Jiawen Kang, Dusit Niyato, Jiayi Zhang, Dong In Kim

Thus, we first apply covert communication into JRC and propose a joint radar and covert communication (JRCC) system to achieve high spectrum utilization and secure data transmission simultaneously.

Autonomous Vehicles

Spoofing-Aware Speaker Verification by Multi-Level Fusion

no code implementations29 Mar 2022 Haibin Wu, Lingwei Meng, Jiawen Kang, Jinchao Li, Xu Li, Xixin Wu, Hung-Yi Lee, Helen Meng

In the second-level fusion, the CM score and ASV scores directly from ASV systems will be concatenated into a prediction block for the final decision.

Speaker Verification

Efficient Federated Learning with Spike Neural Networks for Traffic Sign Recognition

no code implementations28 May 2022 Kan Xie, Zhe Zhang, Bo Li, Jiawen Kang, Dusit Niyato, Shengli Xie, Yi Wu

However, for machine learning-based traffic sign recognition on the Internet of Vehicles (IoV), a large amount of traffic sign data from distributed vehicles is needed to be gathered in a centralized server for model training, which brings serious privacy leakage risk because of traffic sign data containing lots of location privacy information.

Federated Learning Privacy Preserving +1

Tackling Spoofing-Aware Speaker Verification with Multi-Model Fusion

no code implementations18 Jun 2022 Haibin Wu, Jiawen Kang, Lingwei Meng, Yang Zhang, Xixin Wu, Zhiyong Wu, Hung-Yi Lee, Helen Meng

However, previous works show that state-of-the-art ASV models are seriously vulnerable to voice spoofing attacks, and the recently proposed high-performance spoofing countermeasure (CM) models only focus solely on the standalone anti-spoofing tasks, and ignore the subsequent speaker verification process.

Open-Ended Question Answering Speaker Verification

Personalized Saliency in Task-Oriented Semantic Communications: Image Transmission and Performance Analysis

no code implementations25 Sep 2022 Jiawen Kang, Hongyang Du, Zonghang Li, Zehui Xiong, Shiyao Ma, Dusit Niyato, Yuan Li

Semantic communication, as a promising technology, has emerged to break through the Shannon limit, which is envisioned as the key enabler and fundamental paradigm for future 6G networks and applications, e. g., smart healthcare.

Image Retrieval Retrieval

Blockchain for Secure and Efficient Data Sharing in Vehicular Edge Computing and Networks

no code implementations IEEE INTERNET OF THINGS JOURNAL, VOL. 6, NO. 3 2018 Jiawen Kang, Rong Y u, Xumin Huang, Maoqiang Wu, Sabita Maharjan, Member, Shengli Xie, and Y an Zhang, Senior Member, IEEE

Due to limited resources with vehicles, vehicular edge computing and networks (VECONs) i. e., the integration of mobile edge computing and vehicular networks, can provide powerful computing and massive storage resources.

Edge-computing

Semantic-Aware Sensing Information Transmission for Metaverse: A Contest Theoretic Approach

no code implementations23 Nov 2022 Jiacheng Wang, Hongyang Du, Zengshan Tian, Dusit Niyato, Jiawen Kang, Xuemin, Shen

Inspired by emerging semantic communication, in this paper, we propose a semantic transmission framework for transmitting sensing information from the physical world to Metaverse.

Semantic Communications for Wireless Sensing: RIS-aided Encoding and Self-supervised Decoding

no code implementations23 Nov 2022 Hongyang Du, Jiacheng Wang, Dusit Niyato, Jiawen Kang, Zehui Xiong, Junshan Zhang, Xuemin, Shen

To select the task-related signal spectrums for achieving efficient encoding, a semantic hash sampling method is introduced.

Self-Supervised Learning

Wireless Sensing Data Collection and Processing for Metaverse Avatar Construction

no code implementations23 Nov 2022 Jiacheng Wang, Hongyang Du, Xiaolong Yang, Dusit Niyato, Jiawen Kang, Shiwen Mao

We observe that the collected sensing data, i. e., channel state information (CSI), suffers from a phase shift problem, which negatively affects the extraction of user information such as behavior and heartbeat and further deteriorates the avatar construction.

Performance Analysis of Free-Space Information Sharing in Full-Duplex Semantic Communications

no code implementations27 Nov 2022 Hongyang Du, Jiacheng Wang, Dusit Niyato, Jiawen Kang, Zehui Xiong, Dong In Kim, Boon Hee Soong

In this paper, we propose a free-space information sharing mechanism based on full-duplex device-to-device (D2D) semantic communications.

Mixed Reality

When Quantum Information Technologies Meet Blockchain in Web 3.0

no code implementations29 Nov 2022 Minrui Xu, Xiaoxu Ren, Dusit Niyato, Jiawen Kang, Chao Qiu, Zehui Xiong, Xiaofei Wang, Victor C. M. Leung

Therefore, in this paper, we introduce a quantum blockchain-driven Web 3. 0 framework that provides information-theoretic security for decentralized data transferring and payment transactions.

Cloud Computing

Enabling AI-Generated Content (AIGC) Services in Wireless Edge Networks

no code implementations9 Jan 2023 Hongyang Du, Zonghang Li, Dusit Niyato, Jiawen Kang, Zehui Xiong, Xuemin, Shen, Dong In Kim

To achieve efficient AaaS and maximize the quality of generated content in wireless edge networks, we propose a deep reinforcement learning-enabled algorithm for optimal ASP selection.

AnycostFL: Efficient On-Demand Federated Learning over Heterogeneous Edge Devices

no code implementations8 Jan 2023 Peichun Li, Guoliang Cheng, Xumin Huang, Jiawen Kang, Rong Yu, Yuan Wu, Miao Pan

We propose a cost-adjustable FL framework, named AnycostFL, that enables diverse edge devices to efficiently perform local updates under a wide range of efficiency constraints.

Federated Learning

Generative AI-empowered Effective Physical-Virtual Synchronization in the Vehicular Metaverse

no code implementations18 Jan 2023 Minrui Xu, Dusit Niyato, Hongliang Zhang, Jiawen Kang, Zehui Xiong, Shiwen Mao, Zhu Han

Furthermore, we propose a multi-task enhanced auction-based mechanism to match and price AVs and MARs for RSUs to provision real-time and effective services.

Autonomous Vehicles

Generative AI-empowered Simulation for Autonomous Driving in Vehicular Mixed Reality Metaverses

1 code implementation16 Feb 2023 Minrui Xu, Dusit Niyato, Junlong Chen, Hongliang Zhang, Jiawen Kang, Zehui Xiong, Shiwen Mao, Zhu Han

In the vehicular mixed reality (MR) Metaverse, the distance between physical and virtual entities can be overcome by fusing the physical and virtual environments with multi-dimensional communications in autonomous driving systems.

Autonomous Driving Mixed Reality

A Sidecar Separator Can Convert a Single-Talker Speech Recognition System to a Multi-Talker One

no code implementations20 Feb 2023 Lingwei Meng, Jiawen Kang, Mingyu Cui, Yuejiao Wang, Xixin Wu, Helen Meng

Although automatic speech recognition (ASR) can perform well in common non-overlapping environments, sustaining performance in multi-talker overlapping speech recognition remains challenging.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +1

Guiding AI-Generated Digital Content with Wireless Perception

no code implementations26 Mar 2023 Jiacheng Wang, Hongyang Du, Dusit Niyato, Zehui Xiong, Jiawen Kang, Shiwen Mao, Xuemin, Shen

Experiments results verify the effectiveness of the WP-AIGC framework, highlighting its potential as a novel approach for guiding AI models in the accurate generation of digital content.

Deep Generative Model and Its Applications in Efficient Wireless Network Management: A Tutorial and Case Study

no code implementations30 Mar 2023 Yinqiu Liu, Hongyang Du, Dusit Niyato, Jiawen Kang, Zehui Xiong, Dong In Kim, Abbas Jamalipour

With the phenomenal success of diffusion models and ChatGPT, deep generation models (DGMs) have been experiencing explosive growth from 2022.

Management

DADFNet: Dual Attention and Dual Frequency-Guided Dehazing Network for Video-Empowered Intelligent Transportation

no code implementations19 Apr 2023 Yu Guo, Ryan Wen Liu, Jiangtian Nie, Lingjuan Lyu, Zehui Xiong, Jiawen Kang, Han Yu, Dusit Niyato

To eliminate the influences of adverse weather conditions, we propose a dual attention and dual frequency-guided dehazing network (termed DADFNet) for real-time visibility enhancement.

Management object-detection +1

The defender's perspective on automatic speaker verification: An overview

no code implementations22 May 2023 Haibin Wu, Jiawen Kang, Lingwei Meng, Helen Meng, Hung-Yi Lee

Automatic speaker verification (ASV) plays a critical role in security-sensitive environments.

Speaker Verification

Unified Modeling of Multi-Talker Overlapped Speech Recognition and Diarization with a Sidecar Separator

no code implementations25 May 2023 Lingwei Meng, Jiawen Kang, Mingyu Cui, Haibin Wu, Xixin Wu, Helen Meng

Extending on this, we incorporate a diarization branch into the Sidecar, allowing for unified modeling of both ASR and diarization with a negligible overhead of only 768 parameters.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +1

Adversarial Attacks and Defenses for Semantic Communication in Vehicular Metaverses

no code implementations6 Jun 2023 Jiawen Kang, Jiayi He, Hongyang Du, Zehui Xiong, Zhaohui Yang, Xumin Huang, Shengli Xie

In this article, we propose a hierarchical SemCom-enabled vehicular metaverses framework consisting of the global metaverse, local metaverses, SemCom module, and resource pool.

Multi-Agent Deep Reinforcement Learning for Dynamic Avatar Migration in AIoT-enabled Vehicular Metaverses with Trajectory Prediction

no code implementations26 Jun 2023 Junlong Chen, Jiawen Kang, Minrui Xu, Zehui Xiong, Dusit Niyato, Chuan Chen, Abbas Jamalipour, Shengli Xie

Specifically, we propose a model to predict the future trajectories of intelligent vehicles based on their historical data, indicating the future workloads of RSUs. Based on the expected workloads of RSUs, we formulate the avatar task migration problem as a long-term mixed integer programming problem.

Trajectory Prediction

Federated Learning-Empowered AI-Generated Content in Wireless Networks

no code implementations14 Jul 2023 Xumin Huang, Peichun Li, Hongyang Du, Jiawen Kang, Dusit Niyato, Dong In Kim, Yuan Wu

Artificial intelligence generated content (AIGC) has emerged as a promising technology to improve the efficiency, quality, diversity and flexibility of the content creation process by adopting a variety of generative AI models.

Federated Learning

A Revolution of Personalized Healthcare: Enabling Human Digital Twin with Mobile AIGC

no code implementations22 Jul 2023 Jiayuan Chen, Changyan Yi, Hongyang Du, Dusit Niyato, Jiawen Kang, Jun Cai, Xuemin, Shen

To promote the development of this new breed of paradigm, in this article, we propose a system architecture of mobile AIGC-driven HDT and highlight the corresponding design requirements and challenges.

Blockchain-empowered Federated Learning for Healthcare Metaverses: User-centric Incentive Mechanism with Optimal Data Freshness

no code implementations29 Jul 2023 Jiawen Kang, Jinbo Wen, Dongdong Ye, Bingkun Lai, Tianhao Wu, Zehui Xiong, Jiangtian Nie, Dusit Niyato, Yang Zhang, Shengli Xie

Given the revolutionary role of metaverses, healthcare metaverses are emerging as a transformative force, creating intelligent healthcare systems that offer immersive and personalized services.

Decision Making Federated Learning +1

Service Reservation and Pricing for Green Metaverses: A Stackelberg Game Approach

no code implementations9 Aug 2023 Xumin Huang, Yuan Wu, Jiawen Kang, Jiangtian Nie, Weifeng Zhong, Dong In Kim, Shengli Xie

A single-leader multi-follower Stackelberg game is formulated between the MSP and users while each user optimizes an offloading probability to minimize the weighted sum of time, energy consumption and monetary cost.

Total Energy

Vision-based Semantic Communications for Metaverse Services: A Contest Theoretic Approach

no code implementations15 Aug 2023 Guangyuan Liu, Hongyang Du, Dusit Niyato, Jiawen Kang, Zehui Xiong, Boon Hee Soong

The framework provides a novel solution to resource allocation for avatar association in VR environments, ensuring a smooth and immersive experience for all users.

QS-TTS: Towards Semi-Supervised Text-to-Speech Synthesis via Vector-Quantized Self-Supervised Speech Representation Learning

no code implementations31 Aug 2023 Haohan Guo, Fenglong Xie, Jiawen Kang, Yujia Xiao, Xixin Wu, Helen Meng

This paper proposes a novel semi-supervised TTS framework, QS-TTS, to improve TTS quality with lower supervised data requirements via Vector-Quantized Self-Supervised Speech Representation Learning (VQ-S3RL) utilizing more unlabeled speech audio.

Representation Learning Speech Synthesis +2

Generative AI-aided Joint Training-free Secure Semantic Communications via Multi-modal Prompts

no code implementations5 Sep 2023 Hongyang Du, Guangyuan Liu, Dusit Niyato, Jiayi Zhang, Jiawen Kang, Zehui Xiong, Bo Ai, Dong In Kim

The system jointly optimizes the diffusion step, jamming, and transmitting power with the aid of the generative diffusion models, enabling successful and secure transmission of the source messages.

Artificial Intelligence for Web 3.0: A Comprehensive Survey

no code implementations17 Aug 2023 Meng Shen, Zhehui Tan, Dusit Niyato, Yuzhi Liu, Jiawen Kang, Zehui Xiong, Liehuang Zhu, Wei Wang, Xuemin, Shen

Then, we thoroughly analyze the current state of AI technology applications in the four layers of Web 3. 0 and offer some insights into its potential future development direction.

Management

Knowledge Base Aware Semantic Communication in Vehicular Networks

no code implementations21 Sep 2023 Le Xia, Yao Sun, Dusit Niyato, Kairong Ma, Jiawen Kang, Muhammad Ali Imran

Semantic communication (SemCom) has recently been considered a promising solution for the inevitable crisis of scarce communication resources.

Generative AI for Integrated Sensing and Communication: Insights from the Physical Layer Perspective

no code implementations2 Oct 2023 Jiacheng Wang, Hongyang Du, Dusit Niyato, Jiawen Kang, Shuguang Cui, Xuemin Shen, Ping Zhang

In this article, we investigate applications of GAI in the physical layer and analyze its support for integrated sensing and communications (ISAC) systems.

From Generative AI to Generative Internet of Things: Fundamentals, Framework, and Outlooks

no code implementations27 Oct 2023 Jinbo Wen, Jiangtian Nie, Jiawen Kang, Dusit Niyato, Hongyang Du, Yang Zhang, Mohsen Guizani

Generative Artificial Intelligence (GAI) possesses the capabilities of generating realistic data and facilitating advanced decision-making.

Decision Making Management

Resource-efficient Generative Mobile Edge Networks in 6G Era: Fundamentals, Framework and Case Study

no code implementations19 Dec 2023 Bingkun Lai, Jinbo Wen, Jiawen Kang, Hongyang Du, Jiangtian Nie, Changyan Yi, Dong In Kim, Shengli Xie

By integrating Generative Artificial Intelligence (GAI) with mobile edge networks, generative mobile edge networks possess immense potential to enhance the intelligence and efficiency of wireless communication networks.

Acceleration Estimation of Signal Propagation Path Length Changes for Wireless Sensing

no code implementations30 Dec 2023 Jiacheng Wang, Hongyang Du, Dusit Niyato, Mu Zhou, Jiawen Kang, H. Vincent Poor

Furthermore, in multi-target scenarios, the fall detection achieves an average true positive rate of 89. 56% and a false positive rate of 11. 78%, demonstrating its importance in enhancing indoor wireless sensing capabilities.

Activity Recognition

Cross-Speaker Encoding Network for Multi-Talker Speech Recognition

no code implementations8 Jan 2024 Jiawen Kang, Lingwei Meng, Mingyu Cui, Haohan Guo, Xixin Wu, Xunying Liu, Helen Meng

To the best of our knowledge, this work represents an early effort to integrate SIMO and SISO for multi-talker speech recognition.

speech-recognition Speech Recognition

When Large Language Model Agents Meet 6G Networks: Perception, Grounding, and Alignment

no code implementations15 Jan 2024 Minrui Xu, Dusit Niyato, Jiawen Kang, Zehui Xiong, Shiwen Mao, Zhu Han, Dong In Kim, Khaled B. Letaief

AI agents based on multimodal large language models (LLMs) are expected to revolutionize human-computer interaction and offer more personalized assistant services across various domains like healthcare, education, manufacturing, and entertainment.

Language Modelling Large Language Model

Tiny Multi-Agent DRL for Twins Migration in UAV Metaverses: A Multi-Leader Multi-Follower Stackelberg Game Approach

no code implementations18 Jan 2024 Jiawen Kang, Yue Zhong, Minrui Xu, Jiangtian Nie, Jinbo Wen, Hongyang Du, Dongdong Ye, Xumin Huang, Dusit Niyato, Shengli Xie

To address the challenges, we propose a tiny machine learning-based Stackelberg game framework based on pruning techniques for efficient UT migration in UAV metaverses.

Generative AI-Driven Human Digital Twin in IoT-Healthcare: A Comprehensive Survey

no code implementations22 Jan 2024 Jiayuan Chen, You Shi, Changyan Yi, Hongyang Du, Jiawen Kang, Dusit Niyato

The Internet of things (IoT) can significantly enhance the quality of human life, specifically in healthcare, attracting extensive attentions to IoT-healthcare services.

Compressing Deep Reinforcement Learning Networks with a Dynamic Structured Pruning Method for Autonomous Driving

no code implementations7 Feb 2024 Wensheng Su, Zhenni Li, Minrui Xu, Jiawen Kang, Dusit Niyato, Shengli Xie

Our method consists of two steps, i. e. training DRL models with a group sparse regularizer and removing unimportant neurons with a dynamic pruning threshold.

Autonomous Driving

Generative AI for Unmanned Vehicle Swarms: Challenges, Applications and Opportunities

no code implementations28 Feb 2024 Guangyuan Liu, Nguyen Van Huynh, Hongyang Du, Dinh Thai Hoang, Dusit Niyato, Kun Zhu, Jiawen Kang, Zehui Xiong, Abbas Jamalipour, Dong In Kim

For that, this paper aims to provide a comprehensive survey on applications, challenges, and opportunities of GAI in unmanned vehicle swarms.

On-demand Quantization for Green Federated Generative Diffusion in Mobile Edge Networks

no code implementations7 Mar 2024 Bingkun Lai, Jiayi He, Jiawen Kang, Gaolei Li, Minrui Xu, Tao Zhang, Shengli Xie

Federated learning is a promising technique for effectively training GAI models in mobile edge networks due to its data distribution.

Federated Learning Quantization

Blockchain-based Pseudonym Management for Vehicle Twin Migrations in Vehicular Edge Metaverse

no code implementations22 Mar 2024 Jiawen Kang, Xiaofeng Luo, Jiangtian Nie, Tianhao Wu, Haibo Zhou, Yonghua Wang, Dusit Niyato, Shiwen Mao, Shengli Xie

As highly computerized avatars of Vehicular Metaverse Users (VMUs), the Vehicle Twins (VTs) deployed in edge servers can provide valuable metaverse services to improve driving safety and on-board satisfaction for their VMUs throughout journeys.

Edge-computing Management

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