Most users agree to online privacy policies without reading or understanding them, even though these documents govern how personal data is collected, shared, and monetized. Privacy policies are typically long, legally complex, and difficult for non-experts to interpret. This paper presents the Smart Privacy Policy Assistant, an LLM-powered system that automatically ingests privacy policies, extracts and categorizes key clauses, assigns human-interpretable risk levels, and generates clear, concise explanations. The system is designed for real-time use through browser extensions or mobile interfaces, surfacing contextual warnings before users disclose sensitive information or grant risky permissions. We describe the end-to-end pipeline, including policy ingestion, clause categorization, risk scoring, and explanation generation, and propose an evaluation framework based on clause-level accuracy, policy-level risk agreement, and user comprehension.
InsightGUIDE: An Opinionated AI Assistant for Guided Critical Reading of Scientific Literature
Information Management Systems Institute（信息管理系统研究所）；ATHENA Research Centre（ATHENA研究中心）；Department of Informatics and Telecommunications（信息与电信系）；University of the Peloponnese（希腊皮埃里亚大学）
PolyFusionAgent: A Multimodal Foundation Model and Autonomous AI Assistant for Polymer Property Prediction and Inverse Design
Department of Applied Computer Science, The University of Winnipeg（应用计算机科学系，温尼伯大学）；Department of Mechanical Engineering, University of Manitoba（机械工程系，曼尼托巴大学）
RobustMAD: Evaluating Real-World Robustness of Multimodal Small Language Models for Deployable Anomaly Detection Assistants
Singapore University of Technology and Design（新加坡科技设计大学）；Agency for Science, Technology and Research (A*STAR)（新加坡科技研究局）；Nanyang Technological University（南洋理工大学）；Chongqing University（重庆大学）
SmartBench: Evaluating LLMs in Smart Homes with Anomalous Device States and Behavioral Contexts
Tsinghua Shenzhen International Graduate School（清华大学深圳国际研究生院）；Jilin University（吉林大学）；The Chinese University of Hong Kong（香港中文大学）；Pengcheng Laboratory（鹏城实验室）
Open TutorAI: An Open-source Platform for Personalized and Immersive Learning with Generative AI
IRF-SIC Laboratory, Ibnou Zohr University（IRF-SIC实验室，伊本·扎赫尔大学）；Regional Center for Education（教育与培训专业地区中心）；Polydisciplinary Faculty of Taroudant, Ibnou Zohr University（塔鲁旦多学科学院，伊本·扎赫尔大学）；Higher School of Technology of Guelmim, Ibnou Zohr University（盖尔米姆技术高等学校，伊本·扎赫尔大学）；Paragraphe laboratory, Paris 8 and CY Cergy Paris Universities（Paragraphe实验室，巴黎8大学和CY塞克巴黎大学）
ActMem: Bridging the Gap Between Memory Retrieval and Reasoning in LLM Agents
State Key Laboratory for Novel Software Technology, Nanjing University, China（南京大学新型软件技术国家重点实验室）；Alibaba Group, Hangzhou, China（阿里巴巴集团，杭州，中国）；National Institute of Healthcare Data Science, Nanjing University, China（南京大学健康数据科学国家研究院）
Intelligent Personal Assistant (IA), also known as Voice Assistant (VA), has become increasingly popular as a human-computer interaction mechanism. Most smartphones have built-in voice assistants that are granted high privilege, which is able to access system resources and private information. Thus, once the voice assistants are exploited by attackers, they become the stepping stones for the attackers to hack into the smartphones. Prior work shows that the voice assistant can be activated by inter-component communication mechanism, through an official Android API. However, this attack method i…
Digital privacy notices aim to provide users with information to make informed decisions. They are, however, fraught with difficulties. Instead, I propose that data privacy decisions can be understood as an expression of user values. To optimize this value expression, I further propose the creation of a value-centered privacy assistant (VcPA). Here, I preliminary explore how a VcPA could enhance user value expression by utilizing three user scenarios in the context of considering whether or not to download an environmental application, the OpenLitterMap app. These scenarios are conceptually co…
