Category
2,089 papers
The manual labor trap is introduced as an empirically grounded concept that explains why monitoring CSOs tend to remain locked into labor-intensive, low-capacity arrangements.
A three-week diary study with 8 blind users using OLLA, a screen-reader-accessible CUA prototype, collecting 1,258 commands across 12 applications with screenshots, UI trees, model responses, and action traces reveals grounding, planning, constraint-tracking, and termination failures, while interviews reveal beyond-aut...
RecalibrateGPT is a system introducing five cross-turn operators that each target a distinct fatigue type, recalibrating LLM responses through a structured panel by acting on the full conversation history with a single click, suggesting AI fatigue is not just a model-quality issue but an interaction-flow cost that inte...
The emergence of the theorems from sustained human-AI collaboration suggests that involving AI throughout a systematic research program may incubate autonomous scientific breakthroughs.
Reach audiences
Advertise in front of researchers, engineers, and readers.
The cluster analysis of chatbot usage and discussion patterns by users showed that most participants in the unrestricted-mode adopted a direct answer-retrieval strategy, while participants in the Socratic-mode initially attempted to reason through the hints before progressively disengaging, suggesting that the success...
AI Morbidity and Mortality (AI M&M) is intended to complement, rather than replace, model monitoring, patient safety reporting, and regulatory oversight by converting individual AI-in-workflow failures into actionable institutional learning.
A taxonomy of bot species on the news aggregation and social media platform Reddit based on temporal, community, linguistic, and semantic features suggests that online bot populations form evolving digital ecosystems.
With the emergence of Physical AI, artificial intelligence is extending beyond screen-based applications to embodied systems that perceive, interact with, and act in the physical world. Unlike traditional AI, Physical AI operates under real-time safety constraints, continuously interacts with dynamic environments, and...
U-Lens improves verification efficiency and effort allocation, reduced perceived workload, and strengthened support across all three stages of uncertainty management, and reframes uncertainty support for generative AI from text-centered cues to a user-centered process of interpreting, evaluating, and acting on uncertai...
The cross-domain benchmark and the evaluation framework for intelligent synthetic-user evidence is made available on request, so that teams can determine in advance when synthetic-user evidence is safe for decision support and when it is not.
This position paper argues that current approaches to the development and deployment of AI agent systems do not support effective human oversight -- they contribute to its degradation, and recommends design-level affordances and organizational protocols that support overseers in exercising critical judgement and counte...
This work proposes LumiCharge, a novel atomic charge prediction framework that incorporates high-order spherical harmonics convolutions and explicitly models multibody interactions, and demonstrates exceptional extrapolation capability and robustness across molecules of varying sizes, effectively overcoming the limitat...
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.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
