most citedAdversarial Attacks and Defenses for Semantic Communication in Vehicular Metaverses

44 citations · 58 across the 6 of their papers we have counts for

collaborators

6 papers

cs.NI2023

Adaptive Bitrate Video Semantic Communication over Wireless Networks

Wentao Gong, Haonan Tong, Sihua Wang +3

This paper investigates the adaptive bitrate (ABR) video semantic communication over wireless networks. In the considered model, video sensing devices must transmit video semantic…

cs.CR2023★ 44 cited

Adversarial Attacks and Defenses for Semantic Communication in Vehicular Metaverses

Jiawen Kang, Jiayi He, Hongyang Du +4

For vehicular metaverses, one of the ultimate user-centric goals is to optimize the immersive experience and Quality of Service (QoS) for users on board. Semantic Communication (Se…

cs.DC2023★ 11 cited

Distributed Learning over Networks with Graph-Attention-Based Personalization

Zhuojun Tian, Zhaoyang Zhang, Zhaohui Yang +2

In conventional distributed learning over a network, multiple agents collaboratively build a common machine learning model. However, due to the underlying non-i.i.d. data distribut…

quant-ph2023★ 2 cited

Reconfigurable Quantum Internet Service Provider

Zhaohui Yang, Chaohan Cui

With the recent developments in engineering quantum systems, the realization of scalable local-area quantum networks has become viable. However, the design and implementation of a…

cs.IT2023

Self-information Domain-based Neural CSI Compression with Feature Coupling

Ziqing Yin, Renjie Xie, Wei Xu +2

Deep learning (DL)-based channel state information (CSI) feedback methods compressed the CSI matrix by exploiting its delay and angle features straightforwardly, while the measure…

cs.DC2023★ 1 cited

A Generalized Look at Federated Learning: Survey and Perspectives

Taki Hasan Rafi, Faiza Anan Noor, Tahmid Hussain +2

Federated learning (FL) refers to a distributed machine learning framework involving learning from several decentralized edge clients without sharing local dataset. This distribute…