134 citations · 166 across the 8 of their papers we have counts for
8 papers
Efficient Privacy-Preserving Retrieval Augmented Generation with Distance-Preserving Encryption
Huanyi Ye, Jiale Guo, Ziyao Liu +1
RAG has emerged as a key technique for enhancing response quality of LLMs without high computational cost. In traditional architectures, RAG services are provided by a single entit…
A Comprehensive Survey on Benchmarks and Solutions in Software Engineering of LLM-Empowered Agentic System
Jiale Guo, Suizhi Huang, Mei Li +8
The integration of Large Language Models (LLMs) into software engineering has driven a transition from traditional rule-based systems to autonomous agentic systems capable of solvi…
Guaranteeing Data Privacy in Federated Unlearning with Dynamic User Participation
Ziyao Liu, Yu Jiang, Weifeng Jiang +3
Federated Unlearning (FU) is gaining prominence for its capability to eliminate influences of Federated Learning (FL) users' data from trained global FL models. A straightforward F…
Privacy-Preserving Federated Unlearning with Certified Client Removal
Ziyao Liu, Huanyi Ye, Yu Jiang +4
In recent years, Federated Unlearning (FU) has gained attention for addressing the removal of a client's influence from the global model in Federated Learning (FL) systems, thereby…
Decentralized Multimedia Data Sharing in IoV: A Learning-based Equilibrium of Supply and Demand
Jiani Fan, Minrui Xu, Jiale Guo +4
The Internet of Vehicles (IoV) has great potential to transform transportation systems by enhancing road safety, reducing traffic congestion, and improving user experience through…
Differentiated Security Architecture for Secure and Efficient Infotainment Data Communication in IoV Networks
Jiani Fan, Lwin Khin Shar, Jiale Guo +3
This paper aims to provide differentiated security protection for infotainment data communication in Internet-of-Vehicle (IoV) networks. The IoV is a network of vehicles that uses…
Efficient Dropout-resilient Aggregation for Privacy-preserving Machine Learning
Ziyao Liu, Jiale Guo, Kwok-Yan Lam +1
With the increasing adoption of data-hungry machine learning algorithms, personal data privacy has emerged as one of the key concerns that could hinder the success of digital trans…
Privacy-Preserving Aggregation in Federated Learning: A Survey
Ziyao Liu, Jiale Guo, Wenzhuo Yang +3
Over the recent years, with the increasing adoption of Federated Learning (FL) algorithms and growing concerns over personal data privacy, Privacy-Preserving Federated Learning (PP…