This work evaluates ODLMs for multi-modal stress prediction using zero-shot prompting, measuring predictive accuracy alongside latency and throughput, and shows that objective sensor features marginally outperform subjective self-reports on average and that lightweight sub-2B models achieve low latency with predictable...
Ibukunoluwa Soyebo, Alyssa Donawa, Rodrigo Aguilar Barrios et al.· IEEE/ACM International Confe...· 0 citations
Conversational AI agents are increasingly explored as creative partners, yet how conversation design shapes child-AI dialogue in co-creative settings remains underexplored. We present Tinker Tales, a tangible dialogue system for child-AI collaborative storytelling, in which educational frameworks (narrative development...
Nayoung Choi, Jiseung Hong, Peace Cyebukayire et al.· 0 citations
Enterprise Digital Twins (EDTs) promise data-driven decision support at organizational scale, but realizing them requires navigating siloed departments, tacit knowledge, and high-stakes decisions with long-horizon consequences. Existing approaches involve domain experts during model development but focus less on early...
K\'erian Fiter, Adil Lagrou, Franck Dervault et al.· 0 citations
This work compares differences in clues generated by human vs multimodal language models, based on a novel coding rubric for calibrated ambiguity, and finds that models consistently exhibit ambiguity collapse.
Cody Kommers, Ming-Rui Ye, Evelyn Gius et al.· 0 citations
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In bespoke art commissions, laypeople know what they feel but lack the words to specify it: one participant wanted a laid-off truck driver depicted as "a ghost in his own machine" but left the medium, scale, and palette unsaid. We frame this as an articulation bottleneck at an under-served upstream stage: requirement d...
Yu-Chao Wang, Yanhong Lu, Yingjie Victor Chen et al.· 0 citations
Assistants built on large language models are expected to write as their user would, and the dominant approach is single-channel: preferences summarised from conversation history and reinserted into context. This inverts the order of inference. Preferences are the task-dependent surface of a comparatively stable person...
B. Sankar, S. Deepthika, Pawni Yadav et al.· 0 citations
Methods for agentic tooling for automated video editing across three tasks varying in editorial goal, complexity and creativity, namely scene previews, video summaries and cinematic trailers are reported.
Surabhi S. Nath, Kim Ferres, Milan Petrović et al.· 0 citations
Results show that participants perceive differences across personalization levels and evaluate AI-generated advertising imagery most positively at a moderate level of personalization, and high personalization increases perceived personalization, which is positively associated with all three outcome measures, but also i...
Victor Kolominsky-Rabas, Leopold Müller, Claudius Budcke et al.· 0 citations
Personalized marketing can increase customer engagement, satisfaction, and conversion. While existing personalization approaches have become effective at matching the right product to the right customer, the visual representation of advertisements remains generic and only weakly tailored to the individual. Prior resear...
Victor Kolominsky-Rabas, Leopold M\"uller, Claudius Budcke et al.· 0 citations
Generative artificial intelligence (GenAI) is changing how work is organized and performed. Real estate marketing is a prime example of this, yet evidence of GenAI in real estate agents' day-to-day practice remains scarce. In this work, we report on our insights from a German-based empirical study with eleven semi-stru...
Victor Kolominsky-Rabas, Leopold M\"uller, Felicia Perpina et al.· 0 citations
This work establishes a precise definition of AI augmentation comprising six conditions, spanning durable net value, meaningful human control, accountability and recovery, and long-term human development through learning, career pathways, and job purpose, and outlines how organisations, researchers, and government lead...
Civic-Ai Collaboration Jiaying Wu, Caleb Ziems, Raymond Chan et al.· 0 citations
Agentic artificial intelligence (AI) is shifting from decision support to autonomous coordination, challenging established assumptions about managerial authority. This qualitative conceptual paper synthesises recent literature in algorithmic management, organisational theory, and human-computer interaction to examine h...
Kwan Hong TAN· Zenodo (CERN European Organi...· 0 citations
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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