Large Language Models (LLMs) offer powerful capabilities in code generation, natural language understanding, and domain-specific reasoning. Their application to quantum software development remains limited, in part because of the lack of high-quality datasets both for LLM training and as dependable knowledge sources. To bridge this gap, we introduce \textit{PennyLang}, an off-the-shelf, high-quality dataset of 3,347 PennyLane-specific quantum code samples with contextual descriptions, curated from textbooks, official documentation, and open-source repositories. Our contributions are threefold: (1) the creation and open-source release of PennyLang, a purpose-built dataset for quantum programming with PennyLane; (2) a framework for automated quantum code dataset construction that systematizes curation, annotation, and formatting to maximize downstream LLM usability; and (3) a baseline evaluation of the dataset across multiple open-source and commercial models, including ablation studies, all conducted within a retrieval-augmented generation (RAG) pipeline. Using PennyLang with RAG substantially improves performance: for example, Qwen 7B's success rate rises from 8.7% without retrieval to 41.7% with full-context augmentation, and LLaMa 4 improves from 78.8% to 84.8%, while also reducing hallucinations and enhancing quantum code correctness. Moving beyond Qiskit-focused studies, we bring LLM-based tools and reproducible methods to PennyLane for advancing AI-assisted quantum development.
QHackBench: Benchmarking Large Language Models for Quantum Code Generation Using PennyLane Hackathon Challenges
New York University (NYU) Abu Dhabi（纽约大学阿布扎比分校）；Center for Quantum and Topological Systems (CQTS), NYUAD Research Institute, New York University Abu Dhabi（纽约大学阿布扎比分校NYUAD研究所量子与拓扑系统中心）
PennySynth: RAG-Driven Data Synthesis for Automated Quantum Code Generation
eBRAIN Lab, Division of Engineering, New York University Abu Dhabi (NYUAD)（eBRAIN实验室，工程系，纽约大学阿布扎比分校）；Center for Quantum and Topological Systems (CQTS), NYUAD Research Institute（量子与拓扑系统中心（CQTS），NYUAD研究所）；Department of Computer Science and Engineering, NYU Tandon School of Engineering（计算机科学与工程系，纽约大学坦顿工程学院）
Towards Agentic RAG with Deep Reasoning: A Survey of RAG-Reasoning Systems in LLMs
Tsinghua University（清华大学）；University of Illinois Chicago（伊利诺伊大学芝加哥分校）；The University of Tokyo（东京大学）；Peking University（北京大学）；University of Illinois Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校）；University of California, Los Angeles（加利福尼亚大学洛杉矶分校）；HKUST（香港科技大学）
Mathematical Reasoning for Unmanned Aerial Vehicles: A RAG-Based Approach for Complex Arithmetic Reasoning
Department of Computer Science（计算机科学系）；Institute For Artificial Intelligence（人工智能研究所）；Hamm-Lippstadt University of Applied Sciences（哈姆-利普施塔特应用科学大学）；University of Stuttgart（斯图加特大学）
From RAG to Agentic RAG for Faithful Islamic Question Answering
Qatar Computing Research Institute, HBKU, Qatar（卡塔尔计算研究中心，HBKU，卡塔尔）；College of Humanities and Social Sciences, HBKU, Qatar（人文与社会科学学院，HBKU，卡塔尔）；Arab Center for Research and Policy Studies, Qatar（阿拉伯研究中心与政策研究所，卡塔尔）；College of Islamic Studies, HBKU, Qatar（伊斯兰研究学院，HBKU，卡塔尔）；College of Public Policy, HBKU, Qatar（公共政策学院，HBKU，卡塔尔）
SHRAG: AFrameworkfor Combining Human-Inspired Search with RAG
Peoples' Friendship University of Russia (RUDN University)（俄罗斯人民友谊大学）；Joint Institute for Nuclear Research（联合核子研究中心）；Vrije Universiteit Amsterdam（阿姆斯特丹自由大学）；University of Skövde（斯德哥尔摩大学）；Department of AI Convergence（人工智能融合部门）；College of Information Computing（信息计算学院）
Fighting Numerical Hallucinations via Data-centric Compilation for Online Financial QA
Shenzhen Technology University（深圳科技大学）；FiT, Tencent（腾讯金融科技部）；South China University of Technology（华南理工大学）；The Hong Kong University of Science and Technology（香港科学与技术大学）；Huazhong University of Science and Technology（华中科技大学）；McGill University（麦吉尔大学）
Retrieval-Augmented Generation in Medicine: A Scoping Review of Technical Implementations, Clinical Applications, and Ethical Considerations
Duke–NUS Medical School（杜克-新加坡国立大学医学院）；University of Cambridge（剑桥大学）；The University of Tokyo（东京大学）；Singapore General Hospital（新加坡中央医院）；University of Geneva（日内瓦大学）；Duke School of Medicine（杜克大学医学院）；Duke Clinical Research Institute（杜克临床研究所）；Singapore Eye Research Institute（新加坡眼科研究所）；Singapore National Eye Center（新加坡国家眼科中心）；Stanford University（斯坦福大学）；Singapore Health Services（新加坡保健服务集团）；National University of Singapore（新加坡国立大学）
C-3PO: Compact Plug-and-Play Proxy Optimization to Achieve Human-like Retrieval-Augmented Generation
Gaoling School of Artificial Intelligence, Renmin University of China（中国人民大学人工智能学院）；Tongyi Lab（通义实验室）；Soochow University（苏州大学）；University of Oxford（牛津大学）；Tsinghua University（清华大学）
A Multimodal Manufacturing Safety Chatbot: Knowledge Base Design, Benchmark Development, and Evaluation of Multiple RAG Approaches
Farmer School of Business, Miami University（Miami大学农业商学院）；Department of Computer Science and Software Engineering, Miami University（Miami大学计算机科学与软件工程系）；Department of Engineering Technology, Miami University（Miami大学工程技术系）；Department of Mechanical and Manufacturing Engineering, Miami University（Miami大学机械与制造工程系）；Department of Industrial and Systems Engineering, University at Buffalo（University at Buffalo工业与系统工程系）
EventChat: Implementation and user-centric evaluation of a large language model-driven conversational recommender system for exploring leisure events in an SME context
Swiss Federal Institute of Technology, Zurich（苏黎世联邦理工学院）
M3DocDep: Multi-modal, Multi-page, Multi-document Dependency Chunking with Large Vision-Language Models
Human-inspired AI Research, Korea University（韩国大学人智AI研究所）；Computer Science and Engineering, Konkuk University（konkuk大学计算机科学与工程系）；Department of Computer Science and Engineering, Korea University（韩国大学计算机科学与工程系）
VimoRAG: Video-based Retrieval-augmented 3D Motion Generation for Motion Language Models
Harbin Institute of Technology (Shenzhen)（哈尔滨工业大学（深圳））；University of Macau（澳门大学）；University of Surrey（Surrey大学）；Nanjing University（南京大学）；Nanyang Technological University（南洋理工大学）；National University of Singapore（新加坡国立大学）
