6 papers
SensingAgents: A Multi-Agent Collaborative Framework for Robust IMU Activity Recognition
Naiyu Zheng, Tianlong Yu, Haochen Yin +3
Human Activity Recognition (HAR) using Inertial Measurement Unit (IMU) sensors is a cornerstone of mobile health, smart environments, and human-computer interaction. However, curre…
Nesterov-Accelerated Robust Federated Learning Over Byzantine Adversaries
Lihan Xu, Yanjie Dong, Gang Wang +3
We investigate robust federated learning, where a group of workers collaboratively train a shared model under the orchestration of a central server in the presence of Byzantine adv…
CO-PFL: Contribution-Oriented Personalized Federated Learning for Heterogeneous Networks
Ke Xing, Yanjie Dong, Xiaoyi Fan +4
Personalized federated learning (PFL) addresses a critical challenge of collaboratively training customized models for clients with heterogeneous and scarce local data. Conventiona…
Exploring and Mitigating Fawning Hallucinations in Large Language Models
Zixuan Shangguan, Yanjie Dong, Lanjun Wang +3
Large language models (LLMs) have demonstrated exceptional proficiency in language understanding. However, when LLMs align their outputs with deceptive and/or misleading prompts, t…
Fine-Tuning and Deploying Large Language Models Over Edges: Issues and Approaches
Yanjie Dong, Haijun Zhang, Chengming Li +3
Since the release of GPT2-1.5B in 2019, the large language models (LLMs) have evolved from specialized deep models to versatile foundation models. While demonstrating remarkable ze…
Model Splitting Enhanced Communication-Efficient Federated Learning for CSI Feedback
Yanjie Dong, Haijun Zhang, Gaojie Chen +3
Recent advancements have introduced federated machine learning-based channel state information (CSI) compression before the user equipments (UEs) upload the downlink CSI to the bas…