66 citations · 77 across the 19 of their papers we have counts for
7 papers · 1 filter
Fall into a Pit, Gain in a Wit: Cognitive-Guided Harmful Meme Detection via Misjudgment Risk Pattern Retrieval
Wenshuo Wang, Ziyou Jiang, Junjie Wang +6
Internet memes have emerged as a popular multimodal medium, yet they are increasingly weaponized to convey harmful opinions through subtle rhetorical devices like irony and metapho…
VulRTex: A Reasoning-Guided Approach to Identify Vulnerabilities from Rich-Text Issue Report
Ziyou Jiang, Mingyang Li, Guowei Yang +2
Software vulnerabilities exist in open-source software (OSS), and the developers who discover these vulnerabilities may submit issue reports (IRs) to describe their details. Securi…
Demystifying the Lifecycle of Failures in Platform-Orchestrated Agentic Workflows
Xuyan Ma, Xiaofei Xie, Yawen Wang +4
Agentic workflows built on low-code orchestration platforms enable rapid development of multi-agent systems, but they also introduce new and poorly understood failure modes that hi…
Joint-GCG: Unified Gradient-Based Poisoning Attacks on Retrieval-Augmented Generation Systems
Haowei Wang, Rupeng Zhang, Junjie Wang +4
Retrieval-Augmented Generation (RAG) systems enhance Large Language Models (LLMs) by retrieving relevant documents from external corpora before generating responses. This approach…
AdInject: Real-World Black-Box Attacks on Web Agents via Advertising Delivery
Haowei Wang, Junjie Wang, Xiaojun Jia +5
Vision-Language Model (VLM) based Web Agents represent a significant step towards automating complex tasks by simulating human-like interaction with websites. However, their deploy…
One Shot Dominance: Knowledge Poisoning Attack on Retrieval-Augmented Generation Systems
Zhiyuan Chang, Mingyang Li, Xiaojun Jia +5
Large Language Models (LLMs) enhanced with Retrieval-Augmented Generation (RAG) have shown improved performance in generating accurate responses. However, the dependence on externa…
Mimicking the Familiar: Dynamic Command Generation for Information Theft Attacks in LLM Tool-Learning System
Ziyou Jiang, Mingyang Li, Guowei Yang +4
Information theft attacks pose a significant risk to Large Language Model (LLM) tool-learning systems. Adversaries can inject malicious commands through compromised tools, manipula…