6 papers
SIMON: Saliency-aware Integrative Multi-view Object-centric Neural Decoding
YuSheng Lin, Ji-Hwa Tsai, Chun-Shu Wei
Recent EEG-to-image retrieval methods leverage pretrained vision encoders and foveation-inspired priors, but typically assume a fixed, center-focused view. This center bias conflic…
Physical Layer Security Performance of Pinching-Antenna Systems With In-Waveguide Attenuation
Xiaochen Zhang, Haitao Du, Yanyu Cheng +2
Pinching antenna (PA) systems have recently gained significant attention. While their physical-layer security (PLS) is being explored, most studies rely on idealized lossless model…
Tail-Latency-Aware Federated Learning with Pinching Antenna: Latency, Participation, and Placement
Yushen Lin, Zhiguo Ding
Straggler synchronization is a dominant wall-clock bottleneck in synchronous wireless federated learning (FL). Under non-IID data, however, aggressively sampling only fast clients…
Pinching-antenna-enabled Federated Learning: Tail Latency, Participation, and Convergence Analysis
Yushen Lin, Zihan Chen, Zhiguo Ding
Federated learning (FL) in wireless networks is limited by straggler delays from unpredictable channel conditions. In this paper, we investigate the pinching-antenna system (PASS),…
Empowering Large Language Models in Wireless Communication: A Novel Dataset and Fine-Tuning Framework
Yushen Lin, Ruichen Zhang, Wenqi Huang +4
In this work, we develop a specialized dataset aimed at enhancing the evaluation and fine-tuning of large language models (LLMs) specifically for wireless communication application…
Rethinking Clustered Federated Learning in NOMA Enhanced Wireless Networks
Yushen Lin, Kaidi Wang, Zhiguo Ding
This study explores the benefits of integrating the novel clustered federated learning (CFL) approach with non-orthogonal multiple access (NOMA) under non-independent and identical…