34 citations · 42 across the 5 of their papers we have counts for
5 papers
Generating Is Believing: Membership Inference Attacks against Retrieval-Augmented Generation
Yuying Li, Gaoyang Liu, Chen Wang +1
Retrieval-Augmented Generation (RAG) is a state-of-the-art technique that mitigates issues such as hallucinations and knowledge staleness in Large Language Models (LLMs) by retriev…
Boundary Unlearning
Min Chen, Weizhuo Gao, Gaoyang Liu +2
The practical needs of the ``right to be forgotten'' and poisoned data removal call for efficient \textit{machine unlearning} techniques, which enable machine learning models to un…
De-Pois: An Attack-Agnostic Defense against Data Poisoning Attacks
Jian Chen, Xuxin Zhang, Rui Zhang +2
Machine learning techniques have been widely applied to various applications. However, they are potentially vulnerable to data poisoning attacks, where sophisticated attackers can…
Spatial-temporal Conv-sequence Learning with Accident Encoding for Traffic Flow Prediction
Zichuan Liu, Rui Zhang, Chen Wang +2
In an intelligent transportation system, the key problem of traffic forecasting is how to extract periodic temporal dependencies and complex spatial correlations. Current state-of-…
Federated Unlearning
Gaoyang Liu, Xiaoqiang Ma, Yang Yang +2
Federated learning (FL) has recently emerged as a promising distributed machine learning (ML) paradigm. Practical needs of the "right to be forgotten" and countering data poisoning…