5 citations · 5 across the 4 of their papers we have counts for
5 papers
OptiLeak: Efficient Prompt Reconstruction via Reinforcement Learning in Multi-tenant LLM Services
Longxiang Wang, Xiang Zheng, Xuhao Zhang +3
Multi-tenant LLM serving frameworks widely adopt shared Key-Value caches to enhance efficiency. However, this creates side-channel vulnerabilities enabling prompt leakage attacks.…
Feature-based Uncertainty Model for School Choice
Yao Zhang, Makoto Yokoo
In this work, we consider a school choice scenario where a student does not exactly know which college is better for her. Although it is hard for a student to obtain an exact prefe…
T-SKM-Net: Trainable Neural Network Framework for Linear Constraint Satisfaction via Sampling Kaczmarz-Motzkin Method
Haoyu Zhu, Yao Zhang, Jiashen Ren +1
Neural network constraint satisfaction is crucial for safety-critical applications such as power system optimization, robotic path planning, and autonomous driving. However, existi…
Fair Evaluation of Federated Learning Algorithms for Automated Breast Density Classification: The Results of the 2022 ACR-NCI-NVIDIA Federated Learning Challenge
Kendall Schmidt, Benjamin Bearce, Ken Chang +21
The correct interpretation of breast density is important in the assessment of breast cancer risk. AI has been shown capable of accurately predicting breast density, however, due t…
A Survey of Privacy Threats and Defense in Vertical Federated Learning: From Model Life Cycle Perspective
Lei Yu, Meng Han, Yiming Li +8
Vertical Federated Learning (VFL) is a federated learning paradigm where multiple participants, who share the same set of samples but hold different features, jointly train machine…