ReMe: Scaffolding Personalized Cognitive Training via Controllable LLM-Mediated Conversations
Microsoft Research（微软研究院）；Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine（上海交通大学医学院附属上海市精神卫生中心老年精神科）
Zilong Wang, Nan Chen, Luna K. Qiu, Ling Yue, Geli Guo, Yang Ou, Shiqi Jiang, Yuqing Yang, Lili Qiu
Global aging calls for scalable and engaging cognitive interventions. Computerized cognitive training (CCT) is a promising non-pharmacological approach, yet many unsupervised programs rely on rigid, hand-authored puzzles that are difficult to personalize and can hinder adherence. Large language models (LLMs) offer more natural interaction, but their open-ended generation complicates the controlled task structure required for cognitive training. We present ReMe, a web-based framework that scaffolds cognitive training through controllable LLM-mediated conversations, addressing both rigidity in conventional CCT content and the need for conversational controllability. ReMe features a modular Puzzle Engine that represents training activities as reusable puzzle groups specified by structured templates and constraint rules, enabling rapid development of dialogue-based word games and personalized tasks grounded in user context. By integrating personal life logs, ReMe supports Life Recall activities for episodic-memory practice through guided retrieval and progressive cues. A community pilot with 32 adults aged 50+ provides initial feasibility signals.
Staying with the Uncertainty: Uncertainty-Scaffolding Strategies for Artificial Moral Advisors in LLM-to-LLM Simulated Conversations
Centre for Data Futures, The Dickson Poon School of Law, King’s College London（数据未来中心、迪克森·普恩法学院、伦敦国王学院）；Department of Informatics, King’s College London（信息学院、伦敦国王学院）；LangAI, Center for Language AI Research, Tohoku University（LangAI、语言人工智能研究中心、东北大学）；Neukom Institute for Computational Science, Dartmouth College（计算科学尼科姆研究所、达特茅斯学院）
MemOps: Benchmarking Lifecycle Memory Operations in Long-Horizon Conversations
MemTensor (Shanghai) Technology Co., Ltd.（墨天轮（上海）科技有限公司）；The Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州））；Renmin University of China（中国人民大学）
Hidden in Memory: Sleeper Memory Poisoning in LLM Agents
SPAR；ELLIS Institute Tübingen（图宾根ELLIS研究所）；MPI for Intelligent Systems（智能系统马克斯·普朗克研究所）；Tübingen AI Center（图宾根人工智能中心）；APTA；CISPA Helmholtz Center for Information Security（信息安全海德堡中心）
