7 papers · 1 filter
Cost-Efficient Privacy Enforcement for Email-Generating LLM Agents under Strategic Information Requests
Qikun Cai, Tao Huang, Chen Hou
LLM agents now act as delegated communication intermediaries: they read private context, draft messages, and send externally visible emails on behalf of a user. Existing checker-re…
CIPL: A Channel-Aware Framework for Recoverable Privacy Leakage in LLM Agents
Tao Huang, Guosen Wu, Guolong Zheng +5
Privacy leakage in LLM agents is commonly evaluated within individual components such as memory, retrieval, or tool-use pipelines, which makes it difficult to distinguish internal…
A Lightweight Plug-in Gate for Transformer-Based Time-Series Forecasters
Hongkai Zhuang, Tao Huang, Chen Hou
Covariate-rich time-series forecasting requires deciding how external variables enter the target forecasting path. Existing Transformer-based forecasters usually build a covariate…
PAPC: Platform Mediation for Privacy-Propagation Externalities in AI-Mediated Workflows
Tao Huang, Guosen Wu, Chen Hou +1
AI-mediated platforms coordinate work through LLM agents acting for different principals. In these workflows, privacy loss can be created before a final answer appears: a memory wr…
Observable Channels, Not Just Storage: Evaluating Privacy Leakage in LLM Agent Pipelines
Tao Huang, Chen Hou, Guosen Wu +1
Privacy leakage in LLM agents is often studied through individual storage or execution components, such as memory modules, retrieval pipelines, or tool-mediated artifacts. However,…
DP-aware AdaLN-Zero: Taming Conditioning-Induced Heavy-Tailed Gradients in Differentially Private Diffusion
Tao Huang, Jiayang Meng, Xu Yang +2
Condition injection enables diffusion models to generate context-aware outputs, which is essential for many time-series tasks. However, heterogeneous conditional contexts (e.g., ob…
Mitigating Membership Inference in Intermediate Representations with Differentially Private Training
Jiayang Meng, Tao Huang, Chen Hou +2
In Embedding-as-an-Interface (EaaI) settings, pre-trained models are queried for Intermediate Representations (IRs). The distributional properties of IRs can leak training-set memb…