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Preprints

Zhou J; Lu Q; Chen J; Zhu L; Xu X; Xing Z; Harrer S, 2026, A Taxonomy of Architecture Options for Foundation Model-based Agents: Analysis and Decision Model, http://dx.doi.org/10.48550/arxiv.2408.02920

Chen J; Wang Z; Sun J; Xing Z; Lu Q; Huang Q; Xu X; Zhu L, 2026, From Exploration to Revelation: Detecting Dark Patterns in Mobile Apps, http://dx.doi.org/10.48550/arxiv.2411.18084

Klymenko MV; Hoang T; Nguyen H; Wilkinson SA; Goldozian B; Zhenchang X; Lu Q; Usman M; Zhu L, 2026, QUT: A Unit Testing Framework for Quantum Subroutines, http://dx.doi.org/10.48550/arxiv.2509.17538

Lee SU; Zhu L; Shamsujjoha M; Dong L; Lu Q; Chen J; Briand L, 2026, A Structured Approach to Safety Case Construction for AI Systems, http://dx.doi.org/10.48550/arxiv.2601.22773

Zhou G; Han Z; Chen S; Huang B; Zhu L; Liu T; Yao L; Zhang K, 2026, HCVP: Leveraging Hierarchical Contrastive Visual Prompt for Domain Generalization, http://dx.doi.org/10.48550/arxiv.2401.09716

Weytjens H; Xu X; Zhang D; Lu Q; Weber I; Zhu L, 2026, RAGOps: Operating and Managing Retrieval-Augmented Generation Pipelines, http://dx.doi.org/10.2139/ssrn.7353461

Lu Q; Zhao D; Liu Y; Zhang H; Zhu L; Xu X; Shi A; Tan T; Kazman R, 2025, AgentArcEval: An Architecture Evaluation Method for Foundation Model based Agents, http://dx.doi.org/10.48550/arxiv.2510.21031

Yang S; Hu Z; Li X; Wang C; Yu T; Xu X; Zhu L; Yao L, 2025, DrunkAgent: Stealthy Memory Corruption in LLM-Powered Recommender Agents, http://dx.doi.org/10.48550/arxiv.2503.23804

Klymenko M; Hoang T; Wilkinson SA; Goldozian B; Ma S; Xu X; Lu Q; Usman M; Zhu L, 2025, Context-Aware Unit Testing for Quantum Subroutines, http://dx.doi.org/10.48550/arxiv.2506.10348

Xu X; Weytjens H; Zhang D; Lu Q; Weber I; Zhu L, 2025, RAGOps: Operating and Managing Retrieval-Augmented Generation Pipelines, http://dx.doi.org/10.48550/arxiv.2506.03401

Yang Y; Long G; Lu Q; Zhu L; Jiang J; Zhang C, 2025, Federated Low-Rank Adaptation for Foundation Models: A Survey, http://dx.doi.org/10.48550/arxiv.2505.13502

Bano M; Zowghi D; Whittle J; Zhu L; Reeson A; Martin R; Parsons J, 2025, A Qualitative Study of User Perception of M365 AI Copilot, http://dx.doi.org/10.48550/arxiv.2503.17661

Zhou G; Xie S; Hao G-Y; Chen S; Huang B; Xu X; Wang C; Zhu L; Yao L; Zhang K, 2025, Emerging Synergies in Causality and Deep Generative Models: A Survey, http://dx.doi.org/10.48550/arxiv.2301.12351

Tao Z; Pan S; Xing Z; Sun X; Haggag O; Grundy J; Li J; Zhu L, 2025, Privacy Bills of Materials: A Transparent Privacy Information Inventory for Collaborative Privacy Notice Generation in Mobile App Development, http://dx.doi.org/10.48550/arxiv.2501.01131

Xu X; Pautasso C; Lo SK; Zhu L; Lu Q; Weber I, 2025, An Extended Pattern Collection for Blockchain-based Applications, http://dx.doi.org/10.48550/arxiv.2502.16017

Shamsujjoha M; Lu Q; Zhao D; Zhu L, 2025, Swiss Cheese Model for AI Safety: A Taxonomy and Reference Architecture for Multi-Layered Guardrails of Foundation Model Based Agents, http://dx.doi.org/10.48550/arxiv.2408.02205

Lee SU; Perera H; Liu Y; Xia B; Lu Q; Zhu L; Salvado O; Whittle J, 2025, Responsible AI Question Bank: A Comprehensive Tool for AI Risk Assessment, http://dx.doi.org/10.48550/arxiv.2408.11820

Klymenko M; Hoang T; Xu X; Xing Z; Usman M; Lu Q; Zhu L, 2024, Architectural Patterns for Designing Quantum Artificial Intelligence Systems, http://dx.doi.org/10.48550/arxiv.2411.10487

Yuan M; Chen J; Xing Z; Quigley A; Luo Y; Luo T; Mohammadi G; Lu Q; Zhu L, 2024, DesignRepair: Dual-Stream Design Guideline-Aware Frontend Repair with Large Language Models, http://dx.doi.org/10.48550/arxiv.2411.01606

Bano M; Zowghi D; Whittle J; Zhu L; Reeson A; Martin R; Parsons J, 2024, Survey Insights on M365 Copilot Adoption, http://dx.doi.org/10.48550/arxiv.2412.16162

Zhang D; Xia B; Liu Y; Xu X; Hoang T; Xing Z; Staples M; Lu Q; Zhu L, 2024, Privacy and Copyright Protection in Generative AI: A Lifecycle Perspective, http://dx.doi.org/10.48550/arxiv.2311.18252

Liu Y; Lo SK; Lu Q; Zhu L; Zhao D; Xu X; Harrer S; Whittle J, 2024, Agent Design Pattern Catalogue: A Collection of Architectural Patterns for Foundation Model based Agents, http://dx.doi.org/10.48550/arxiv.2405.10467

Perera H; Lee SU; Liu Y; Xia B; Lu Q; Zhu L; Cairns J; Nottage M, 2024, Achieving Responsible AI through ESG: Insights and Recommendations from Industry Engagement, http://dx.doi.org/10.48550/arxiv.2409.10520

Lee SU; Perera H; Liu Y; Xia B; Lu Q; Zhu L; Cairns J; Nottage M, 2024, Integrating ESG and AI: A Comprehensive Responsible AI Assessment Framework, http://dx.doi.org/10.48550/arxiv.2408.00965

Hu Z; Wang C; Shu Y; Helen ; Paik ; Zhu L, 2024, Prompt Perturbation in Retrieval-Augmented Generation based Large Language Models, http://dx.doi.org/10.48550/arxiv.2402.07179

Hu Z; Wang C; Helen ; Paik ; Shu Y; Zhu L, 2024, Learning Interpretable Scheduling Algorithms for Data Processing Clusters, http://dx.doi.org/10.48550/arxiv.2405.19131

Xia B; Lu Q; Zhu L; Xing Z, 2024, An AI System Evaluation Framework for Advancing AI Safety: Terminology, Taxonomy, Lifecycle Mapping, http://dx.doi.org/10.48550/arxiv.2404.05388

Lu Q; Zhu L; Xu X; Xing Z; Harrer S; Whittle J, 2024, Towards Responsible Generative AI: A Reference Architecture for Designing Foundation Model based Agents, http://dx.doi.org/10.48550/arxiv.2311.13148

Liu Y; Lu Q; Zhu L; Paik H-Y, 2024, Decentralised Governance-Driven Architecture for Designing Foundation Model based Systems: Exploring the Role of Blockchain in Responsible AI, http://dx.doi.org/10.48550/arxiv.2308.05962

Zhang D; Pan S; Hoang T; Xing Z; Staples M; Xu X; Yao L; Lu Q; Zhu L, 2024, To Be Forgotten or To Be Fair: Unveiling Fairness Implications of Machine Unlearning Methods, http://dx.doi.org/10.48550/arxiv.2302.03350

Shanmugarasa Y; Chamikara MAP; Paik H-Y; Kanhere SS; Zhu L, 2023, Local Differential Privacy for Smart Meter Data Sharing, http://dx.doi.org/10.48550/arxiv.2311.04544

Lu Q; Zhu L; Xu X; Whittle J; Zowghi D; Jacquet A, 2023, Responsible AI Pattern Catalogue: A Collection of Best Practices for AI Governance and Engineering, http://dx.doi.org/10.48550/arxiv.2209.04963

Zhuo TY; Du X; Xing Z; Sun J; Quan H; Li L; Zhu L, 2023, Pop Quiz! Do Pre-trained Code Models Possess Knowledge of Correct API Names?, http://dx.doi.org/10.48550/arxiv.2309.07804

Zhou G; Huang C; Chen X; Xu X; Wang C; Zhu L; Yao L, 2023, Contrastive Counterfactual Learning for Causality-aware Interpretable Recommender Systems, http://dx.doi.org/10.48550/arxiv.2208.06746

Hoang T; Dam HK; Bi T; Lu Q; Xing Z; Zhu L; Nguyen LD; Chen S, 2023, Quantum Software Analytics: Opportunities and Challenges, http://dx.doi.org/10.48550/arxiv.2307.11305

Lee SU; Perera H; Xia B; Liu Y; Lu Q; Zhu L; Salvado O; Whittle J, 2023, QB4AIRA: A Question Bank for AI Risk Assessment, http://dx.doi.org/10.48550/arxiv.2305.09300

Lo SK; Liu Y; Yu G; Lu Q; Xu X; Zhu L, 2023, Distributed Trust Through the Lens of Software Architecture, http://dx.doi.org/10.48550/arxiv.2306.08056

Xie M; Xing Z; Feng S; Chen C; Zhu L; Xu X, 2023, Psychologically-Inspired, Unsupervised Inference of Perceptual Groups of GUI Widgets from GUI Images, http://dx.doi.org/10.48550/arxiv.2206.10352

Xia B; Lu Q; Perera H; Zhu L; Xing Z; Liu Y; Whittle J, 2023, Towards Concrete and Connected AI Risk Assessment (C$^2$AIRA): A Systematic Mapping Study, http://dx.doi.org/10.48550/arxiv.2301.11616

Lo SK; Lu Q; Paik H-Y; Zhu L, 2023, Decision Models for Selecting Federated Learning Architecture Patterns, http://dx.doi.org/10.48550/arxiv.2204.13291

Sanderson C; Lu Q; Douglas D; Xu X; Zhu L; Whittle J, 2023, Towards Implementing Responsible AI, http://dx.doi.org/10.48550/arxiv.2205.04358

Nguyen LT; Nguyen LD; Hoang T; Bandara D; Wang Q; Lu Q; Xu X; Zhu L; Popovski P; Chen S, 2023, Blockchain-Empowered Trustworthy Data Sharing: Fundamentals, Applications, and Challenges, http://dx.doi.org/10.48550/arxiv.2303.06546

Xia B; Bi T; Xing Z; Lu Q; Zhu L, 2023, An Empirical Study on Software Bill of Materials: Where We Stand and the Road Ahead, http://dx.doi.org/10.48550/arxiv.2301.05362

Liu Y; Lu Q; Yu G; Paik H-Y; Zhu L, 2022, BGRA: A Reference Architecture for Blockchain Governance, http://dx.doi.org/10.48550/arxiv.2211.04811

Liu Y; Lu Q; Yu G; Paik H-Y; Perera H; Zhu L, 2022, A Pattern Language for Blockchain Governance, http://dx.doi.org/10.48550/arxiv.2203.00268

Liu Y; Lu Q; Yu G; Paik H-Y; Zhu L, 2022, Defining Blockchain Governance Principles: A Comprehensive Framework, http://dx.doi.org/10.48550/arxiv.2110.13374

Liu Y; Lu Q; Zhu L; Paik H-Y; Staples M, 2022, A Systematic Literature Review on Blockchain Governance, http://dx.doi.org/10.48550/arxiv.2105.05460

Lu Q; Zhu L; Xu X; Whittle J; Douglas D; Sanderson C, 2021, Software Engineering for Responsible AI: An Empirical Study and Operationalised Patterns, http://dx.doi.org/10.48550/arxiv.2111.09478

Lo SK; Liu Y; Lu Q; Wang C; Xu X; Paik H-Y; Zhu L, 2021, Blockchain-based Trustworthy Federated Learning Architecture, http://dx.doi.org/10.48550/arxiv.2108.06912

Lu Q; Xu X; Bandara HMND; Chen S; Zhu L, 2021, Patterns for Blockchain-Based Payment Applications, http://dx.doi.org/10.48550/arxiv.2102.09810


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