Large language model (LLM)-based student simulation offers a scalable alternative for educational research, teacher training, and learner practice. However, its validity depends on whether LLMs maintain stable personas across and within interactions. We test this using a dual-assessment framework measuring self-reporte...
Jana Gonnermann-M\"uller, Jennifer Haase, Nicolas Leins et al.· 0 citations
Work on morality in large language models (LLMs) has progressed via constitutional AI, reinforcement learning from human feedback (RLHF) and systematic benchmarking, yet it still lacks tools to connect internal moral representations to regulatory obligations, to design cultural plurality across the full development sta...
Large Language Model-based voice assistants (LLM-VAs) have shown potential to support older adults aging in place through proactive reminders, health information, and everyday assistance. As LLM-VAs become more conversational, designing explanations of their behavior requires understanding what information they communi...
Shared co-creative workspaces allow users to contribute while agents execute. Yet how users adjust their participation as their work and the agent's execution shape one another remains less understood. We conducted two design probe studies with professional designers. In Study 1 (N=10), participants identified opportun...
Kihoon Son, Hyewon Lee, DaEun Choi et al.· 0 citations
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We investigate how large language models can be used as research tools in scientific computing while preserving mathematical rigor. We propose a human-in-the-loop workflow for interactive theorem proving and discovery with LLMs. Human experts retain control over problem formulation and assumptions, while the model sear...
Chenyi Li, Zhijian Lai, Dong An et al.· 0 citations
The carbon intensity of electric-vehicle (EV) charging varies over time and place, yet EV charging recommender systems and eco-routing interfaces rarely make this variation actionable for drivers. We investigate how renewable-energy information interacts with two attributes that routinely shape public-charging decision...
Delong Du, Apostolos Vavouris, Omid Veisi et al.· 0 citations
Robotic pets for older adults are typically studied as companions, with the older person positioned as the robot's primary interaction partner. This framing overlooks another role: a petlike robot can mediate relationships between people. We report a formative qualitative interview study with six adults aged 63-77 in G...
Delong Du, Sara Gilda Amirhajlou, Akwasi Gyabaah et al.· 0 citations
Therapeutic writing offers significant benefits for well-being; however, for family caregivers, conventional fixed or user-initiated schedules often fail to align with their dynamic, high-stress reality. We conducted a three-week field study with 47 caregivers using a chatbot that delivered daily reflective writing cue...
Shunpei Norihama, Yuka Iwane, Jo Takezawa et al.· 0 citations
Artificial intelligence (AI) increasingly shapes how people think, engage, and evaluate information. To minimize risk, most current systems are designed to present as ideologically neutral with standardized output. Yet growing evidence suggests that these principles suppress cognitive engagement, impair human decision-...
Shiyang Lai, Jiwoong Choi, Junsol Kim et al.· 0 citations
EEG based multi-dimension emotion recognition has attracted substantial research interest in affective computing. However, the high dimensionality of EEG features, coupled with limited sample sizes, frequently leads to classifier overfitting and high computational complexity. Feature selection constitutes a critical st...
Xueyuan Xu, Tianze Yu, Junming Zhang et al.· 0 citations
Artificial intelligence (AI) registers and inventories aim to make governmental AI visible, but their institutional scope, schemas, and reporting practices construct different representations of public-sector AI. We compare 8,368 records from country-specific and transnational inventories covering 72 countries. Across...
Body-cue recognition can support assistive robots, but benchmark accuracy does not guarantee reliable behavior under a robot-camera viewpoint. We present Nuni, a bedside robot prototype that treats a detected distress cue as a reason to ask rather than a reason to alert. We compare two X3D-UGT RGB appearance classifier...
Students in MIT’s Concourse program delve deeply into the human condition, debate challenging questions, and learn to develop judgment about issues that can’t be quantified.
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity. The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduSep 30, 2026
Able to defeat top-ranked human players and more efficient than other models, the new system could help decision-makers in military maneuvers or business negotiations.
Computer scientist, entrepreneur, and philanthropist will collaborate with the MIT Schwarzman College of Computing to advance AI and scientific discovery.
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