175 citations · 562 across the 37 of their papers we have counts for
6 papers · 1 filter
PSGraph: Differentially Private Streaming Graph Synthesis by Considering Temporal Dynamics
Quan Yuan, Zhikun Zhang, Linkang Du +6
Streaming graphs are ubiquitous in daily life, such as evolving social networks and dynamic communication systems. Due to the sensitive information contained in the graph, directly…
SoK: Dataset Copyright Auditing in Machine Learning Systems
Linkang Du, Xuanru Zhou, Min Chen +5
As the implementation of machine learning (ML) systems becomes more widespread, especially with the introduction of larger ML models, we perceive a spring demand for massive data.…
NeRF: Privacy-preserving Training Framework for NeRF
Bokang Zhang, Yanglin Zhang, Zhikun Zhang +3
Neural Radiance Fields (NeRF) have revolutionized 3D computer vision and graphics, facilitating novel view synthesis and influencing sectors like extended reality and e-commerce. H…
Real-Time Trajectory Synthesis with Local Differential Privacy
Yujia Hu, Yuntao Du, Zhikun Zhang +4
Trajectory streams are being generated from location-aware devices, such as smartphones and in-vehicle navigation systems. Due to the sensitive nature of the location data, directl…
DPAdapter: Improving Differentially Private Deep Learning through Noise Tolerance Pre-training
Zihao Wang, Rui Zhu, Dongruo Zhou +4
Recent developments have underscored the critical role of \textit{differential privacy} (DP) in safeguarding individual data for training machine learning models. However, integrat…
TrustLLM: Trustworthiness in Large Language Models
Yue Huang, Lichao Sun, Haoran Wang +67
Large language models (LLMs), exemplified by ChatGPT, have gained considerable attention for their excellent natural language processing capabilities. Nonetheless, these LLMs prese…