9 papers
When Non-Adversarial Noise Hurts Learning: Benchmarking Skill Self-Evolution in Agents
Tao Yu, Zhongtian Luo, Yuchen Long +19
Large language model agents increasingly improve by distilling experience into reusable skills, but errors in that experience can persist in learned rules and affect later tasks. E…
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…
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…
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…
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…
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…
Improving Deepfake Detection with Reinforcement Learning-Based Adaptive Data Augmentation
Yuxuan Zhou, Tao Yu, Wen Huang +3
The generalization capability of deepfake detectors is critical for real-world use. Data augmentation via synthetic fake face generation effectively enhances generalization, yet cu…
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 various attack strategies that bypass the safety mechanisms of VLMs. Among thes…
BrowserAgent: Building Web Agents with Human-Inspired Web Browsing Actions
Tao Yu, Zhengbo Zhang, Zhiheng Lyu +8
Efficiently solving real-world problems with LLMs increasingly hinges on their ability to interact with dynamic web environments and autonomously acquire external information. Whil…