collaborators

15 papers

cs.CR2026

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…

cs.CV2026

VeriDrive: Verifiable Counterfactual Supervision for Cost-Efficient Vision-Language Planning

Zikai Zhang, Hubert P. H. Shum, Toby P. Breckon

Vision-language driving models increasingly use reasoning supervision to bridge perception, prediction, and planning, but existing driving rationales are often free-form and expens…

cs.CR2026

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…

cs.CL2026

Majority Bit-Aware Watermarking For Large Language Models

Jiahao Xu, Rui Hu, Olivera Kotevska +1

The growing deployment of Large Language Models (LLMs) has raised concerns about their misuse in generating harmful or deceptive content. To address this issue, watermarking method…

cs.CL2026

XMark: Reliable Multi-Bit Watermarking for LLM-Generated Texts

Jiahao Xu, Rui Hu, Olivera Kotevska +1

Multi-bit watermarking has emerged as a promising solution for embedding imperceptible binary messages into Large Language Model (LLM)-generated text, enabling reliable attribution…

cs.AR2026

ROMA: a Read-Only-Memory-based Accelerator for QLoRA-based On-Device LLM

Wenqiang Wang, Yijia Zhang, Zikai Zhang +4

As large language models (LLMs) demonstrate powerful capabilities, deploying them on edge devices has become increasingly crucial, offering advantages in privacy and real-time inte…