3 papers
cs.CR2026
PRAG: Efficient Privacy-Preserving RAG Service Supporting Arbitrary Top- Retrieval
Yulong Ming, Mingyue Wang, Jijia Yang +4
Retrieval-Augmented Generation (RAG) enables large language models to use external knowledge, but outsourcing the RAG service raises privacy concerns for both data owners and users…
cs.LG2025
LiveVal: Time-aware Data Valuation via Adaptive Reference Points
Jie Xu, Zihan Wu, Cong Wang +1
Time-aware data valuation enhances training efficiency and model robustness, as early detection of harmful samples could prevent months of wasted computation. However, existing met…
cs.LG2024
LMEraser: Large Model Unlearning through Adaptive Prompt Tuning
Jie Xu, Zihan Wu, Cong Wang +1
To address the growing demand for privacy protection in machine learning, we propose a novel and efficient machine unlearning approach for \textbf{L}arge \textbf{M}odels, called \t…