81 citations · 210 across the 12 of their papers we have counts for
12 papers
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…
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…
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Incorporating external knowledge has emerged as a promising way to mitigate outdated knowledge and hallucinations in LLM.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…
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…
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…
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…
Nighthawk: Fully Automated Localizing UI Display Issues via Visual Understanding
Zhe Liu, Chunyang Chen, Junjie Wang +3
Graphical User Interface (GUI) provides a visual bridge between a software application and end users, through which they can interact with each other. With the upgrading of mobile…
Guided Bug Crush: Assist Manual GUI Testing of Android Apps via Hint Moves
Zhe Liu, Chunyang Chen, Junjie Wang +3
Mobile apps are indispensable for people's daily life. Complementing with automated GUI testing, manual testing is the last line of defence for app quality. However, the repeated a…
Identifying Emergent Leadership in OSS Projects Based on Communication Styles
Yuekai Huang, Ye Yang, Junjie Wang +2
In open source software (OSS) communities, existing leadership indicators are dominantly measured by code contribution or community influence. Recent studies on emergent leadership…
Owl Eyes: Spotting UI Display Issues via Visual Understanding
Zhe Liu, Chunyang Chen, Junjie Wang +3
Graphical User Interface (GUI) provides a visual bridge between a software application and end users, through which they can interact with each other. With the development of techn…