5 citations · 9 across the 14 of their papers we have counts for
4 papers · 1 filter
Vision Token Manipulation Attacks on Cloud-Edge Inference of Large Vision-Language Models
Zikai Zhang, Rui Hu, Olivera Kotevska +1
Cloud-edge Large Vision-Language Model (LVLM) inference enables efficient deployment by splitting computation between edge devices and cloud servers. In this process, intermediate…
SelfGrader: LLM Jailbreak Detection via Anchored Token-Level Logits
Zikai Zhang, Rui Hu, Olivera Kotevska +1
Large Language Models (LLMs) are powerful tools for answering user queries, yet they remain highly vulnerable to jailbreak attacks. Existing guardrail methods typically rely on int…
Optimal Client Sampling in Federated Learning with Client-Level Heterogeneous Differential Privacy
Jiahao Xu, Rui Hu, Olivera Kotevska
Federated Learning with client-level differential privacy (DP) provides a promising framework for collaboratively training models while rigorously protecting clients' privacy. Howe…
Traceable Black-box Watermarks for Federated Learning
Jiahao Xu, Rui Hu, Olivera Kotevska +1
Due to the distributed nature of Federated Learning (FL) systems, each local client has access to the global model, which poses a critical risk of model leakage. Existing works hav…