Co-Annotator is presented, which distills expert gaze and dictation into two guidance components: a gaze-aligned Vision Transformer producing fixation-aligned areas of interest (AOIs), and an ontology-bounded vision-language model (VLM) that pre-fills editable biomarker summaries for retinal optical coherence tomograph...
ZihengLeoLi, Benjamin Freeman, Akshay Raman et al.· 0 citations
The findings suggest that ADBA offers solid advantages to the traditional PINs, and successfully addresses the tradeoffs between efficiency, memorability, and security under the usage scenarios considered in the study.
Yuxuan Huang, Qiao Jin, Tongyu Nie et al.· 0 citations
FISICA is a body-assessment and recommendation service running in production that measures the avatar with the same function used on the subject and solves until the two agree, on a sampling-invariant spinal metric.
Juhwan Song, Heejung Kim, Jun Hee Noh et al.· 0 citations
GuardianAgent, a policy-conditioned anonymization framework that couples structured risk assessment with verified adaptive rewriting, achieves the strongest privacy-utility trade-off among published baselines and is the only method to reach more than 0.90 privacy in all three domains, remaining robust under a backbone...
Rui-Yi Yang, Gayathri Lihinikaduarachchi, Rahat Masood et al.· 0 citations
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FlowCheck, a constraint language to specify user-visible information flows directly through the application interface, where constraints can also be displayed and inspected without reading code, and are structured enough for reliable LLM generation.
Reya Vir, Lydia B. Chilton, Zhuo Zhang et al.· Proceedings of the 2nd ACM S...· 2 citations
When 54 international experts assessed AI-generated disinformation threats, they revealed a surprising pattern: while video deepfakes received the highest average threat ratings in the political domain (M = 6.31/7), the pattern differed in the health domain, where AI-generated text received the highest average rating (...
Alexander Loth, Martin Kappes, Marc-Oliver Pahl· Harvard Kennedy School Misin...· 1 citation
InsightToast is introduced, a mixed-initiative application that monitors verbal discourse in real time, identifies topics and informational needs as they emerge, and proactively retrieves relevant information through a multi-agent large language model (LLM)-based pipeline integrating retrieval-augmented generation (RAG...
Mohammad Abolnejadian, Matthew Brehmer· 0 citations
This work introduces LipCoder, a voice-centric programming toolkit designed to deliver editor-level functionality through auditory and speech-based interfaces, and quantitative trends and qualitative feedback point to directions for auditory-first design that may broaden accessibility in speech-driven coding environmen...
Hayoon Kim, Sung-Ho Lee, Juhwi Kim et al.· 0 citations
It is shown that rankings alone can guide generation under limited conditions, while transferable criterion inference remains constrained by the foundation model's ability to recognize, reason about, and verbalize musical attributes.
Futaba Hidaka, Naomi Imasato, Kazuki Miyazawa et al.· 0 citations
This work bridges the gap between affective computing and technical implementation of autonomous vehicles, grounding UX evaluation in real-world contexts and laying a foundation for user-centered design of autonomous mobility systems and robotics in general.
Helen Schneider, Svetlana Pavlitska, J. M. Zöllner· 0 citations
It is suggested that cognitive processes can provide a promising basis for support selection in proactive writing systems and is hypothesized that Flower and Hayes' cognitive process theory of writing offers an interpretable bridge between observable writing behavior and appropriate support types.
Masahiro Yoshida, Atsuya Kobayashi, Kei Tateno et al.· 0 citations
DOBI (Dynamic Opportunistic Body Input), a real-time XR technique that uses gaze to target a UI element, a brief trigger gesture to identify the recruited spare body region, and the region's subsequent motion to drive continuous 1D control, is presented.
Rachel Kim, Qi-Feng Xun, Sang Ho Yoon· 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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