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2,089 papers
Reproducibility checks during peer review require a shared understanding of what authors'code is expected to reproduce. We present an author-in-the-loop collaborative audit that makes author declarations explicit inputs to an AI agent's investigation and assessment. A structured checklist records reproduction instructi...
This first comprehensive analysis of consent and data collection practices across 10,000+ mHealth apps on the Google Play Store is presented, combining static analysis and privacy policy examination, with a rigorous operational definition to distinguish health apps from general wellness programs, and a measurement fram...
Multisensory XR may support informal learning for autistic adults, but sensory-friendly design often emphasizes reducing input. We conducted a mixed-methods, counterbalanced within-subjects study with 20 Chinese autistic adults who evaluated five complete XR configurations presenting the same popular-science content. C...
This work surveyed 331 software developers at Microsoft about what AI lets them do that they could not do before and analyzed their answers using reflexive thematic analysis with a human-in-the-loop, multi-model AI council.
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A multi-stage spatial trajectory reconstruction algorithm that extracts frequency-domain features to identify handwriting regions and achieve high-precision reconstruction of 3D word trajectories is designed, and a novel spatial-to-visual mapping algorithm is introduced, which bridges the gap between spatial trajectory...
It is suggested that natural, behavior-based feedback maintains the illusion of conversing with a thinking entity, while technical indicators expose the computational substrate in AI agents.
Enterprise data assistants using large language models (LLMs) promise democratized data access in organizations. Yet in our real-world deployment within the CFO unit's data lake at an industry partner, we observed that business users frequently pose imperfect prompts that include domain-specific vocabulary and lack sch...
Ubiquitous computing has long pursued Weiser's vision of technologies that "disappear" into everyday life. As wearable health systems advance, they increasingly substitute for rather than scaffold users' judgment, yet the long-term consequences remain underexplored. We report an eight-year, five-wave longitudinal inter...
Data exposure is situate as a central interaction problem in end-of-life ubiquitous computing and design implications for interpretive stability, care-context alignment, and existential support are derived.
Prompt engineering is commonly understood as a technical practice aimed at eliciting useful, accurate, and appropriately structured outputs from large language models (LLMs). Yet prompts do more than optimize model performance: they shape what information is elicited, which assumptions are introduced, and which perspec...
Artificial intelligence (AI) for Science is often described as a progression from human-directed assistance toward increasingly autonomous AI scientists. Human-AI collaboration offers a further mode in which human and AI contributions substantively shape scientific reasoning, judgments, and the course of inquiry. Exist...
YouTube has many features, such as homepage recommendations, that encourage users to explore its vast library of videos. However, when users visit YouTube with a specific intention, e.g., learning how to program in Python, these features to encourage exploration are often distracting. Prior work has innovated 'commitme...
AI agents can generate code at a scale that’s hard for humans to review line-by-line. PDD Kit helps ensure the code is doing what the developer intended by creating formal specifications and testing against them. It converts developer intent into a Verus specification, proves AI-generated code meets it for every input, and uses tests where proofs aren't practical. Developers review intent, not every line. The post Formally verifying agent-written full-stack web apps with PDD Kit appeared first o…
Data Mining & Modeling
Professor Paris Smaragdis develops computers with superhuman hearing for applications like speech recognition, music understanding, and environmental monitoring.
During the School of Humanities, Arts, and Social Sciences’ 75th Anniversary Symposium, President Sally Kornbluth said “MIT has never needed your particular insight and guidance more than we do now.”
Assistant Professor Benjamin Lindquist studies how engineers deliberately injected randomness into early AI, giving rise to deep-learning models that sometimes hallucinate.
“X-Hinges” helps design and 3D print items like lamps and gloves with an interactive twist: automatically embedded sensors that perceive and adaptively respond to human contact.
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