University stakeholders often face difficulties in accessing timely and reliable information, especially in developing countries, where there are very few intelligent support systems. Existing rule-based chatbots are unable to handle complex, domain-specific queries and are not well-equipped to adapt to evolving institutional policies. As a fill-in-the-gap solution, we present the multimodal university chatbot with retrieval-augmented generation. The system combines the large language model with semantic retrieval to produce context-based responses from institution-centric resources, such as the university handbook. The system accepts text and image queries through the vision-language model and applies quantized inference for rapid deployment on constrained hardware. A scalable backend built with FastAPI, adjoined with a responsive frontend developed with Next.js, ensures real-time usability. Our multimodal evaluation demonstrates that the system maintains strong satisfaction scores across both text and image queries, despite increased response time for visual inputs. Furthermore, quantitative evaluation shows that hallucination is reduced from 31.7% to 6.6% in our proposed RAG-based system, confirming the effectiveness of retrieval grounding.
CRISS: A Retrieval-Augmented AI Chatbot for Assisting Cancer Registrars
University of Missouri（密苏里大学）；Missouri Cancer Registry and Research Center（密苏里癌症登记与研究中心）；MU Institute for Data Science and Informatics（密苏里大学数据科学与信息学研究所）
Chat2Scenic: An Iterative RAG-Based Framework for Scenario Generation in Autonomous Driving
Technical University of Munich（慕尼黑工业大学）；Munich Institute of Robotics and Machine Intelligence (MIRMI)（慕尼黑机器人与机器智能研究所）；University College London（伦敦大学学院）
ChatPlanner: A Large Language Model Framework for Personalized Public Transit Routing
School of Engineering and Materials Science, Queen Mary University of London（伦敦玛丽女王大学工程与材料科学学院）；Department of Engineering Science, University of Oxford（牛津大学工程科学系）
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）
An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability
University of Southern California（南加州大学）；Stevens Institute of Technology（史蒂文斯理工学院）；Virginia Tech（弗吉尼亚理工大学）
本文通过 NASA 太空任务设计挑战实证评估 ChatGPT-3.5 在任务工程问题表述中识别利益相关者的能力，发现其对人本利益相关者识别较好但对环境因素识别差、抽象层次保持不足且并行输出变异性大，表明其可靠性有限。
Privacy Challenges and Solutions in Retrieval-Augmented Generation-Enhanced LLMs for Healthcare Chatbots: A Review of Applications, Risks, and Future Directions
Centre for Smart Health, School of Nursing（智能健康中心、护理学院）；The Hong Kong Polytechnic University（香港理工大学）；Department of Electrical and Electronic Engineering（电子与电气工程系）；Faculty of Health Sciences（健康科学学院）；University of Maribor（马里博大学）
Demo: Guide-RAG: Evidence-Driven Corpus Curation for Retrieval-Augmented Generation in Long COVID
Department of Computer Science University of Texas at Austin（计算机科学系得克萨斯大学奥斯汀分校）；School of Information University of Texas at Austin（信息学院得克萨斯大学奥斯汀分校）；McCombs School of Business University of Texas at Austin（麦库姆斯商学院得克萨斯大学奥斯汀分校）；Dell Medical School University of Texas at Austin（德克萨斯大学奥斯汀分校戴尔医学学院）
COMPARE: Clinical Optimization with Modular Planning and Assessment via RAG-Enhanced AI-OCT: Superior Decision Support for Percutaneous Coronary Intervention Compared to ChatGPT-5 and Junior Operators
Tangdu Hospital, The Fourth Military Medical University（空军军医大学唐都医院）；Research Institute of Tsinghua University in Shenzhen（深圳清华大学研究院）；The Second Affiliated Hospital, Air Force Medical University（空军军医大学第二附属医院）
Ethical ChatGPT: Concerns, Challenges, and Commandments
Data Science Institute, University of Technology Sydney（悉尼科技大学数据科学学院）；Medical University Graz（格拉茨医科大学）；University of Natural Resources and Life Sciences Vienna（维也纳自然资源与生命科学大学）
