Many Security Operations Centers rely on signature-based Network Intrusion Detection Systems like Suricata, yet detection rule engineering remains understudied. We investigate this process by introducing SuriCap, a platform for rule engineering exercises, and hosting CTF-style workshops where 60 participants, trained M...
Koen T. W. Teuwen, Emmanuele Zambon, Luca Allodi· 0 citations
The application of machine learning to molecular property prediction has become increasingly prevalent in drug discovery, yet most models operate as black boxes, returning a prediction without revealing which structural features drive it. MolExplain addresses this gap by combining property prediction with sub-structure...
Footnotes can be powerful tools to aid understanding, providing information that augments the reading experience. However, static footnotes cannot address every reader question. Current reading tools allow readers to view curated footnotes, allow personal and social annotation, and link dictionaries to reading material...
Piper Vasicek, Courtni Byun, Kevin Seppi· 0 citations
This work introduces E3Sense, a head-worn platform that co-locates electroencephalography, eye tracking, and electrodermal activity to personalize engagement measurement and provides a proof-of-concept of a head-site, personalized multimodal sensing of engagement for adaptive educational interfaces.
Sidharth Anupkrishnan, Itir Sayar, Jeongah Lee et al.· 0 citations
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Lifelong learners from different industries often watch the same recorded lecture, even when they will apply the material in different workplaces. We present Bespoke, a system that takes the transcript of an existing lecture and generates a new video customized to a target industry and duration, with new slides, narrat...
Romain Puech, Dewang Kumar Agarwal, Antonio Santamar\'ia Escobar et al.· 0 citations
AI assistants that support email composition may shift cultural communication norms, such as the directness typical of low-context cultures like the US versus the indirectness and contextual sensitivity central to high-context cultures like Japan. Yet it remains unknown to what extent people adopt and edit AI drafts in...
Shintaro Sakai, Alice Gao, Yuichi Shoda et al.· 0 citations
Cybersickness remains a major barrier for the adoption of virtual reality (VR), yet most existing knowledge is derived from laboratory-based studies with relatively small and homogeneous participant samples. In this paper, we investigate whether remote VR studies can produce cybersickness findings comparable to traditi...
Matt Gottsacker, Gerd Bruder, Daniel Zielasko et al.· 0 citations
Recent work reports that vision--language models (VLMs) struggle to establish and maintain stable reference in repeated reference games. Rather than ask which VLM does best, we ask a more basic question: do you need a large pretrained VLM for this at all? On grounding a single director utterance to one of twelve tangra...
HCI and HRI studies often require short, repeatable arousal manipulations that can run while participants continue interacting with a device or robot. These experiments are often challenged by the need to induce arousal in settings that still resemble real interaction. Participants must continue using a device, touchin...
Prolonged sedentary behavior, a pervasive issue in modern workplaces, has been closely linked to musculoskeletal disorders (MSDs) and reduced productivity. This study evaluates the effectiveness of Deep Care Isa, an advanced digital health assistant, in addressing these challenges. Utilizing data from over 2,300 partic...
Quanmin Liang, Junjie Yang, Mohammad Ali Nasseri et al.· 0 citations
The analysis shows that participants rarely treated LLMs as autonomous storytellers, and that LLM assistance is most productive after human seeding and constraint-setting, and that it shifts labor from production to verification.
Zhuo-Jun Jiang, Yuki Ueno, Chris Bryan· 0 citations
Surgical videos are a primary resource for teaching trainees anatomy, tool usage, and procedural skills. Yet learning from them at scale requires systems that understand surgical scenes. Existing approaches fall short: vision-language models lack fine-grained domain reasoning, task-specific models do not generalize, an...
Jingying Wang, Rosiana Natalie, Marquise D Singleterry 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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