collaborators

8 papers

cs.CR2026

A Multimodal Automatic Redteaming Evaluation based on Atomic Jailbreak Strategy Decoupling and Combination

Shiji Zhao, Yuxuan Zhou, Chen Xiong +3

Multimodal Large Language Models (MLLMs) have achieved impressive progress in image-text comprehension and generation, yet they remain susceptible to jailbreak attacks that can tri…

cs.CV2026

IDO: Incongruity-aware Distribution Optimization for Multimodal Fake News Detection

Hengyang Zhou, Rongman Hong, Yuxuan Zhou +2

Multimodal fake news detection aims to identify the authenticity of news. Existing multimodal fake news detection methods mainly focus on cross-modal consistency, but often fail to…

cs.SD2026

Omni-DeepSearch: A Benchmark for Audio-Driven Omni-Modal Deep Search

Tao Yu, yiming ding, Shenghua Chai +16

Current omni-modal benchmarks mainly evaluate models under settings where multiple modalities are provided simultaneously, while the ability to start from audio alone and actively…

cs.MA2026

Beyond the All-in-One Agent: Benchmarking Role-Specialized Multi-Agent Collaboration in Enterprise Workflows

Tao Yu, Hao Wang, Changyu Li +15

Large language model (LLM) agents are increasingly expected to operate in enterprise environments, where work is distributed across specialized roles, permission-controlled systems…

cs.CR2025

Why does weak-OOD help? A Further Step Towards Understanding Jailbreaking VLMs

Yuxuan Zhou, Yuzhao Peng, Yang Bai +7

Large Vision-Language Models (VLMs) are susceptible to jailbreak attacks: researchers have developed a variety of attack strategies that can successfully bypass the safety mechanis…

cs.CR2025

JPRO: Automated Multimodal Jailbreaking via Multi-Agent Collaboration Framework

Yuxuan Zhou, Yang Bai, Kuofeng Gao +2

The widespread application of large VLMs makes ensuring their secure deployment critical. While recent studies have demonstrated jailbreak attacks on VLMs, existing approaches are…