54 citations · 235 across the 31 of their papers we have counts for
31 papers
From Failed Trajectories to Reliable LLM Agents: Diagnosing and Repairing Harness Flaws
Mengzhuo Chen, Junjie Wang, Zhe Liu +3
LLM agents increasingly rely on agent harness: the runtime infrastructure around the base model that defines execution environments, tool interfaces, context, lifecycle orchestrati…
OrchJail: Jailbreaking Tool-Calling Text-to-Image Agents by Orchestration-Guided Fuzzing
Jianming Chen, Yawen Wang, Junjie Wang +3
Tool-calling text-to-image (T2I) agents can plan and execute multi-step tool chains to accomplish complex generation and editing queries. However, this capability introduces a new…
Seeing the Whole Elephant: A Benchmark for Failure Attribution in LLM-based Multi-Agent Systems
Mengzhuo Chen, Junjie Wang, Fangwen Mu +4
Failure attribution, i.e., identifying the responsible agent and decisive step of a failure, is particularly challenging in LLM-based multi-agent systems (MAS) due to their natural…
From Flat Logs to Causal Graphs: Hierarchical Failure Attribution for LLM-based Multi-Agent Systems
Yawen Wang, Wenjie Wu, Junjie Wang +1
LLM-powered Multi-Agent Systems (MAS) have demonstrated remarkable capabilities in complex domains but suffer from inherent fragility and opaque failure mechanisms. Existing failur…
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…
Understanding Individual Agent Importance in Multi-Agent System via Counterfactual Reasoning
Jianming Chen, Yawen Wang, Junjie Wang +4
Explaining multi-agent systems (MAS) is urgent as these systems become increasingly prevalent in various applications. Previous work has proveided explanations for the actions or s…
What External Knowledge is Preferred by LLMs? Characterizing and Exploring Chain of Evidence in Imperfect Context for Multi-Hop QA
Zhiyuan Chang, Mingyang Li, Xiaojun Jia +5
Incorporating external knowledge has emerged as a promising way to mitigate outdated knowledge and hallucinations in LLM. However, external knowledge is often imperfect, encompassi…
From Allies to Adversaries: Manipulating LLM Tool-Calling through Adversarial Injection
Haowei Wang, Rupeng Zhang, Junjie Wang +4
Tool-calling has changed Large Language Model (LLM) applications by integrating external tools, significantly enhancing their functionality across diverse tasks. However, this inte…
Adversarial Robustness of Open-source Text Classification Models and Fine-Tuning Chains
Hao Qin, Mingyang Li, Junjie Wang +1
Context:With the advancement of artificial intelligence (AI) technology and applications, numerous AI models have been developed, leading to the emergence of open-source model host…
Repairing Catastrophic-Neglect in Text-to-Image Diffusion Models via Attention-Guided Feature Enhancement
Zhiyuan Chang, Mingyang Li, Junjie Wang +3
Text-to-Image Diffusion Models (T2I DMs) have garnered significant attention for their ability to generate high-quality images from textual descriptions. However, these models ofte…
A Roadmap for Software Testing in Open Collaborative Development Environments
Qing Wang, Junjie Wang, Mingyang Li +2
Amidst the ever-expanding digital sphere, the evolution of the Internet has not only fostered an atmosphere of information transparency and sharing but has also sparked a revolutio…
Unblind Text Inputs: Predicting Hint-text of Text Input in Mobile Apps via LLM
Zhe Liu, Chunyang Chen, Junjie Wang +5
Mobile apps have become indispensable for accessing and participating in various environments, especially for low-vision users. Users with visual impairments can use screen readers…
VEglue: Testing Visual Entailment Systems via Object-Aligned Joint Erasing
Zhiyuan Chang, Mingyang Li, Junjie Wang +2
Visual entailment (VE) is a multimodal reasoning task consisting of image-sentence pairs whereby a promise is defined by an image, and a hypothesis is described by a sentence. The…
Adversarial Testing for Visual Grounding via Image-Aware Property Reduction
Zhiyuan Chang, Mingyang Li, Junjie Wang +4
Due to the advantages of fusing information from various modalities, multimodal learning is gaining increasing attention. Being a fundamental task of multimodal learning, Visual Gr…
Play Guessing Game with LLM: Indirect Jailbreak Attack with Implicit Clues
Zhiyuan Chang, Mingyang Li, Yi Liu +3
With the development of LLMs, the security threats of LLMs are getting more and more attention. Numerous jailbreak attacks have been proposed to assess the security defense of LLMs…
Make LLM a Testing Expert: Bringing Human-like Interaction to Mobile GUI Testing via Functionality-aware Decisions
Zhe Liu, Chunyang Chen, Junjie Wang +5
Automated Graphical User Interface (GUI) testing plays a crucial role in ensuring app quality, especially as mobile applications have become an integral part of our daily lives. De…
Testing the Limits: Unusual Text Inputs Generation for Mobile App Crash Detection with Large Language Model
Zhe Liu, Chunyang Chen, Junjie Wang +5
Mobile applications have become a ubiquitous part of our daily life, providing users with access to various services and utilities. Text input, as an important interaction channel…
CrashTranslator: Automatically Reproducing Mobile Application Crashes Directly from Stack Trace
Yuchao Huang, Junjie Wang, Zhe Liu +5
Crash reports are vital for software maintenance since they allow the developers to be informed of the problems encountered in the mobile application. Before fixing, developers nee…
Software Testing with Large Language Models: Survey, Landscape, and Vision
Junjie Wang, Yuchao Huang, Chunyang Chen +3
Pre-trained large language models (LLMs) have recently emerged as a breakthrough technology in natural language processing and artificial intelligence, with the ability to handle l…
Chatting with GPT-3 for Zero-Shot Human-Like Mobile Automated GUI Testing
Zhe Liu, Chunyang Chen, Junjie Wang +5
Mobile apps are indispensable for people's daily life, and automated GUI (Graphical User Interface) testing is widely used for app quality assurance. There is a growing interest in…
Fill in the Blank: Context-aware Automated Text Input Generation for Mobile GUI Testing
Zhe Liu, Chunyang Chen, Junjie Wang +4
Automated GUI testing is widely used to help ensure the quality of mobile apps. However, many GUIs require appropriate text inputs to proceed to the next page which remains a promi…
The Metamorphosis: Automatic Detection of Scaling Issues for Mobile Apps
Yuhui Su, Chunyang Chen, Junjie Wang +4
As the bridge between users and software, Graphical User Interface (GUI) is critical to the app accessibility. Scaling up the font or display size of GUI can help improve the visua…