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1,682 papers
Background-adaptive contrast enhancement thus becomes part of the object's compositing properties, reducing the design and maintenance of separate color variants, and is implemented in the same WebGL pipeline, with no sustained additional runtime observed.
MedVA is presented, an end-to-end neuro-symbolic agentic system for medical volume visualization that addresses limitations through three complementary agents and provides more complete, clinically grounded ROI specifications than MLLM-only reasoning.
As conversational AI systems increasingly operate in sensitive domains, the central challenge shifts from usability to trust calibration, ensuring that users rely on systems neither too much nor too little. Systems that provide advice or interpretations risk encouraging inappropriate reliance, particularly when users p...
This work introduces the CAST framework to connect measurement choices with person-specific models of exposure, behavior, physiology, and experience and proposes four synchronized measurement modules linking mobile and wearable data with self-reports and intervention responses.
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Existing Parsons problem tools primarily focus on correctness, indicating whether a student solved a problem, but providing limited visibility into the underlying problem-solving process. We address this gap by introducing Pulla, a Parsons problem tool that instruments programming assignments to capture fine-grained in...
An in-the-wild study of task planning using time-stamped logs of 24,265 tasks from 957 users of a widely used daily planner app, observed over six weeks alongside self-reported surveys to support evaluating planning tools across the task lifecycle.
The findings inform timely, comprehensible support and reassuring social presence in simulated dental VR; they concern the complete package rather than individual modules or clinical effectiveness.
Durable skills, such as collaboration, creativity and critical thinking, are instrumental to success in the modern workforce. Yet, measuring these skills remains a persistent challenge. Moreover, because what is not measured is often not taught, these skills are often overlooked in mainstream educational curricula. Des...
Most knowledge of graphical perception comes from behavioral studies. Understanding from a neural perspective is much more limited due in part to neuroimaging studies' expensiveness and difficulty to conduct. In this paper, we evaluate whether Meta's Tribe V2 neural encoding model can recover neural contrasts from a vi...
Botto is often described as a decentralized autonomous artist, but its authorship cannot be located in image generation alone. This paper examines Botto as an agentic curatorial system in which generation, ranking, voting, feedback, and minting form a recursive loop. Drawing on Botto's documentation and prior accounts...
AI model updates and service withdrawals can disrupt relationships with AI companions, but research has largely examined individual platform events. Less is known about users' responses when multiple providers implement shared national regulations. We examine users' reactions and collective contestation surrounding Chi...
Can interacting with someone from 1930, with no knowledge of what happened after, influence a person's perception of the past? People reason about the present against a picture of the past without observing it. The past is reconstructed from memory and testimony, but this reconstruction has been filtered through everyt...
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.
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.
A Blog post by H company on Hugging Face
The PKG Center for Social Impact expands Code.Tulsa experiential learning program.
Computer scientist, entrepreneur, and philanthropist will collaborate with the MIT Schwarzman College of Computing to advance AI and scientific discovery.
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