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1,707 papers
This work analyzes the DiversityOne dataset, comprising four weeks of passive smartphone sensing and ecological momentary assessments collected from 453 university students across eight countries, and extracts behavioral features spanning dietary habits, physical activity, screen time, and smartphone usage, and investi...
This paper sketches a starting point for task design and measurement signals grounded in drama therapy's existing use of role and aesthetic distance, and raises provocations for workshop discussion: the observer effect and privacy paradox that measurement introduces, and the question of whose lens the gap is.
GazeDepth is introduced, an eye-tracking dataset collected from 19 participants using a wearable tracker during tasks reflecting real-world scenarios that captures gaze characteristics that distinguish the three viewing-distance categories, supporting gaze-based distance inference and distance-aware interaction in real...
Findings show that hand-anchored abstract visual cues provide a lightweight means of externalizing object tactile state, reducing information asymmetry without compromising social presence.
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It is found that LLMs outperform expectations at replicating comment structure and formality, but struggle to accurately capture nuanced emotions, e.g. understating joy and overstating anger.
Building effective AI systems increasingly depends on writing high-quality task requirements, yet users often struggle to articulate the constraints, preferences, and edge cases that determine success. This problem is especially acute in AI development, where behavior is shaped not only by human expectations but also b...
It is argued that for applications processing sensitive user data (medical, legal, journalistic, or personal), the Web-CLI should be the default architecture, as it makes data locality an independently verifiable technical property rather than a policy promise.
A provenance-aware pipeline that converts task telemetry and human-authored reports into a shared typed task-state representation, aligns and reconciles their facts, detects conflicts, and generates structured handover reports supports provenance-aware state reconciliation as a design pattern for safer AI-assisted hand...
This work model the AI-mediated process of writing a student--instructor email at the highest level of involvement, and compares it with an unaided model of writing the same messages, built from participants' accounts and a classic model of the writing process.
A minimal seven-field curatable record is derived and complementary responsibilities for model hubs, scholarly indexes, and digital libraries are derived, providing practical guidance for improving the preservation and bibliographic control of open LLM artifacts.
Data Characters is introduced, a visualization approach that represents affective content in journaling through human-like characters and investigates the potential of character-based representations for conveying affective experiences and explores what visual encodings emerge through customization.
A preliminary framework for analyzing adaptability in cooperative games by conceptualizing adaptive stimuli as retrieval or disruption of players'ludic knowledge is presented and offered an initial vocabulary for describing how cooperative games can be designed to create demands for team adaptation.
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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