19 citations · 73 across the 32 of their papers we have counts for
33 papers
SpreadMark: Robust Image Watermarking via Spread-Spectrum Embedding
Wei Song, Yuxin Cao, Zhenchang Xing +4
Invisible image watermarks are increasingly used for deepfake detection and provenance tracking, where they must survive not only incidental distortions but also deliberate removal…
LEGOUI: Designing with UI-DSL Bricks to Balance Transparency and Controllability
Yinsi Zhou, Mingyue Yuan, Hongyue Xu +8
Generative user interface design tools enable rapid prototyping but often operate as black boxes with limited transparency and controllability. When outputs diverge from the design…
Interpretable Column Annotation with LLM-Symbolized Decision Process Materialization
Mengqi Wang, Jianwei Wang, Qing Liu +5
Column annotation (CA), including column type annotation (CTA) and column property annotation (CPA), aims to identify the meanings of table columns and the semantic relationships a…
TRACE: A Two-Channel Robust Attribution Watermark via Complementary Embeddings for LLM-Agent Trajectories
Zheng Gao, Xiaoyu Li, Xiaoyan Feng +5
LLM agents reach users through resellers, who may rebrand a developer's agent or substitute a cheaper model. When provenance is disputed, attribution rests on the trajectory log (t…
Still Manual? Automated Linter Configuration via DSL-Based LLM Compilation of Coding Standards
Zejun Zhang, Yixin Gan, Zhenchang Xing +5
Coding standards are essential for maintaining consistent and high-quality code across teams and projects. Linters help developers enforce these standards by detecting code violati…
DeMark: A Query-Free Black-Box Attack on Deepfake Watermarking Defenses
Wei Song, Zhenchang Xing, Liming Zhu +2
The rapid proliferation of realistic deepfakes has raised urgent concerns over their misuse, motivating the use of defensive watermarks in synthetic images for reliable detection a…
Ensembling LLM-Induced Decision Trees for Explainable and Robust Error Detection
Mengqi Wang, Jianwei Wang, Qing Liu +5
Error detection (ED), which aims to identify incorrect or inconsistent cell values in tabular data, is important for ensuring data quality. Recent state-of-the-art ED methods lever…
QUT: A Unit Testing Framework for Quantum Subroutines
Mykhailo V. Klymenko, Thong Hoang, Hoa Nguyen +6
We present the architectural design and prototype implementation of QUT (Quantum Unit Testing), a framework for unit testing of quantum subroutines. The framework is developed with…
PTMPicker: Facilitating Efficient Pretrained Model Selection for Application Developers
Pei Liu, Terry Zhuo, Jiawei Deng +4
The rapid emergence of pretrained models (PTMs) has attracted significant attention from both Deep Learning (DL) researchers and downstream application developers. However, selecti…
LLM-based HSE Compliance Assessment: Benchmark, Performance, and Advancements
Jianwei Wang, Mengqi Wang, Yinsi Zhou +5
Health, Safety, and Environment (HSE) compliance assessment demands dynamic real-time decision-making under complicated regulations and complex human-machine-environment interactio…
A Case Study of Scalable Content Annotation Using Multi-LLM Consensus and Human Review
Mingyue Yuan, Jieshan Chen, Zhenchang Xing +2
Content annotation at scale remains challenging, requiring substantial human expertise and effort. This paper presents a case study in code documentation analysis, where we explore…
SeeAction: Towards Reverse Engineering How-What-Where of HCI Actions from Screencasts for UI Automation
Dehai Zhao, Zhenchang Xing, Qinghua Lu +2
UI automation is a useful technique for UI testing, bug reproduction, and robotic process automation. Recording user actions with an application assists rapid development of UI aut…
FactFlow: Automatic Fact Sheet Generation and Customization from Tabular Dataset via AI Chain Design & Implementation
Minh Duc Vu, Jieshan Chen, Zhenchang Xing +3
With the proliferation of data across various domains, there is a critical demand for tools that enable non-experts to derive meaningful insights without deep data analysis skills.…
Explore-Construct-Filter: An Automated Framework for Rich and Reliable API Knowledge Graph Construction
Yanbang Sun, Qing Huang, Xiaoxue Ren +3
The API Knowledge Graph (API KG) is a structured network that models API entities and their relations, providing essential semantic insights for tasks such as API recommendation, c…
Architectural Patterns for Designing Quantum Artificial Intelligence Systems
Mykhailo Klymenko, Thong Hoang, Xiwei Xu +4
Utilising quantum computing technology to enhance artificial intelligence systems is expected to improve training and inference times, increase robustness against noise and adversa…
DesignRepair: Dual-Stream Design Guideline-Aware Frontend Repair with Large Language Models
Mingyue Yuan, Jieshan Chen, Zhenchang Xing +6
The rise of Large Language Models (LLMs) has streamlined frontend interface creation through tools like Vercel's V0, yet surfaced challenges in design quality (e.g., accessibility,…
Automated Soap Opera Testing Directed by LLMs and Scenario Knowledge: Feasibility, Challenges, and Road Ahead
Yanqi Su, Zhenchang Xing, Chong Wang +4
Exploratory testing (ET) harnesses tester's knowledge, creativity, and experience to create varying tests that uncover unexpected bugs from the end-user's perspective. Although ET…
Towards Human-AI Synergy in UI Design: Supporting Iterative Generation with LLMs
Mingyue Yuan, Jieshan Chen, Yongquan Hu +5
In automated UI design generation, a key challenge is the lack of support for iterative processes, as most systems focus solely on end-to-end output. This stems from limited capabi…
A Layered Architecture for Developing and Enhancing Capabilities in Large Language Model-based Software Systems
Dawen Zhang, Xiwei Xu, Chen Wang +2
Significant efforts has been made to expand the use of Large Language Models (LLMs) beyond basic language tasks. While the generalizability and versatility of LLMs have enabled wid…
From Exploration to Revelation: Detecting Dark Patterns in Mobile Apps
Jieshan Chen, Zhen Wang, Jiamou Sun +5
Mobile apps are essential in daily life but frequently employ deceptive patterns, such as visual emphasis or linguistic nudging, to manipulate user behavior. Existing research larg…
Evaluation-Driven Development and Operations of LLM Agents: A Process Model and Reference Architecture
Boming Xia, Qinghua Lu, Liming Zhu +3
Large Language Models (LLMs) have enabled the emergence of LLM agents, systems capable of pursuing under-specified goals and adapting after deployment. Evaluating such agents is ch…
A Taxonomy of Architecture Options for Foundation Model-based Agents: Analysis and Decision Model
Jingwen Zhou, Qinghua Lu, Jieshan Chen +4
The rapid advancement of AI technology has led to widespread applications of agent systems across various domains. However, the need for detailed architecture design poses signific…
An AI System Evaluation Framework for Advancing AI Safety: Terminology, Taxonomy, Lifecycle Mapping
Boming Xia, Qinghua Lu, Liming Zhu +1
The advent of advanced AI underscores the urgent need for comprehensive safety evaluations, necessitating collaboration across communities (i.e., AI, software engineering, and gove…
GPTVoiceTasker: Advancing Multi-step Mobile Task Efficiency Through Dynamic Interface Exploration and Learning
Minh Duc Vu, Han Wang, Zhuang Li +4
Virtual assistants have the potential to play an important role in helping users achieves different tasks. However, these systems face challenges in their real-world usability, cha…