Rapid eating is common yet difficult to regulate in situ, partly because people seldom notice pace changes and sustained self-monitoring is effortful. We present Earinter, a commodity-earbud-based closed-loop system that integrates in-the-wild sensing, real-time reasoning, and theory-grounded just-in-time (JIT) interve...
Jun Fang, Ka I Chan, Xiyuxing Zhang et al.· 0 citations
This work understands robots in public spaces not in terms of autonomy or intelligence, but as a relational capacity, which implies designing robots not in the authors' image or for their utility, but grounded in their needs in being and becoming together.
Victor Tuan Vu Pham, Judith Dörrenbächer, Thomas H. Weisswange et al.· 0 citations
A Kinematics-Aware Decoupled Learning Network for robust 3D hand pose estimation and a task-decoupled hierarchical multitask framework, which separates 2D joint localization from depth estimation and incorporates a dedicated multitask learning strategy for depth regression.
Jun Lu, Zhen-Ming Chen, Lin Chen et al.· 0 citations
The Causal Context-Gated Forecaster (CCGF), which encodes a 60-frame pre-dropout history of gaze and head pose and combines it with DINOv3 scene features and evaluates two scene conditions: Live, in which the scene representation continues to update during tracker loss, and Frozen, in which the final pre-dropout repres...
Shabnam Shabani, G. Farhani· 0 citations
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This work investigated post-task workflows: editable, graph-based representations of an agent's completed execution that improve their understanding and error detection over a prompt-only condition, and found that validation succeeded mainly when users cross-checked across multiple evidence sources.
Ze-Kun Wu, Xin-Ru Wang, Rock Yuren Pang et al.· 0 citations
Scholars have long proposed third-party middleware as an alternative to centralized algorithmic feeds: feeds built and distributed by independent feed creators. This vision saw no large-scale instantiation until Bluesky, a decentralized microblogging platform, introduced custom feeds in 2023. Although central to the mi...
Neurosurgeons frequently interact with operating room (OR) technologies while sterility and occupied hands constrain control. We introduce earables as a direct, hands-free control platform for neurosurgery using tooth-click input. Formative OR observations and interviews with 10 domain experts grounded the design. Usin...
Jonas Hummel, Maximilian Burzer, Clara Sayffaerth et al.· 0 citations
Freelance game coaches monetize their gaming expertise by offering personalized instruction to players seeking to improve, working through gig platforms, yet little is known about how they operate. To address this gap, we conducted semi-structured interviews with 20 experienced freelance coaches across 17 competitive g...
This work explores laughter as a naturally occurring, sparse index for constructing contextualized personal records to support later reconstruction and reflection and inform self-tracking designs that use sparse affective indices to organize contextual records for reconstruction and reflection.
Jun Fang, Jia-Jin Li, Yun-Tao Wang et al.· 0 citations
In human-LLM content co-generation, AI-generated information can enter final artifacts without being adequately processed by users, creating risks when artifacts are shared or acted upon. We study whether recognition-level uptake of atomic information units can be assessed in open-ended co-generation and predicted from...
Yu Mei, Fengyou Zu, Ruiwen Zhang et al.· 0 citations
Investigation of how communication should adapt to event priority and passenger activity highlights event consequence, passenger activity, continuing information value, and confirmation need as key considerations for selective in-cabin communication.
CoNS-Explorer is developed, which uses reviewed instructional DAGs/SCMs to maintain a shared causal-fact ledger and generate fact-matched direct explanations and contextualized stories and four testable design propositions for adaptive causal explanation.
Bo-Wen Deng, Jian-Qing Zou, Ke-Xin Zhang et al.· 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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