most citedA Learning-based Incentive Mechanism for Mobile AIGC Service in Decentralized Internet of Vehicles

8 citations · 13 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CR2026

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…

cs.CR2024

Efficient Federated Unlearning with Adaptive Differential Privacy Preservation

Yu Jiang, Xindi Tong, Ziyao Liu +3

Federated unlearning (FU) offers a promising solution to effectively address the need to erase the impact of specific clients' data on the global model in federated learning (FL),…

cs.CR2024★ 1 cited

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…

cs.AI2024★ 8 cited

A Learning-based Incentive Mechanism for Mobile AIGC Service in Decentralized Internet of Vehicles

Jiani Fan, Minrui Xu, Ziyao Liu +4

Artificial Intelligence-Generated Content (AIGC) refers to the paradigm of automated content generation utilizing AI models. Mobile AIGC services in the Internet of Vehicles (IoV)…

cs.CR2024★ 4 cited

Threats, Attacks, and Defenses in Machine Unlearning: A Survey

Ziyao Liu, Huanyi Ye, Chen Chen +2

Machine Unlearning (MU) has recently gained considerable attention due to its potential to achieve Safe AI by removing the influence of specific data from trained Machine Learning…