Virtual Reality (VR) is changing how we interact with complex spatial datasets. VR has the potential within forestry to help analyse remotely sensed spatial data for inventory management. However, challenges of scale and legibility of dense forest point clouds must be addressed. To do so, we present three VR Focus+Cont...
Spencer O'Keeffe, Jan Rombouts, Bruce H Thomas et al.· 0 citations
Transcutaneous Electrical Stimulation (TES) for stress modulation has largely focused on vagus nerve stimulation at the neck, yet two questions remain underexplored: how users experience electrotactile sensations at this sensitive site, and whether electrotactile feedback itself can function as a haptic stress interven...
Yoon Kyung Shon (University of Maryland), Pablo E. Paredes (University of Maryland)· 0 citations
Presence-aware intelligence is the capacity of an AI system's intelligence layer to adapt appropriately to the functional state of the person it serves (here readiness, flow, and stability) while preserving task quality and safety. We introduce PresenceBench, an instrument for measuring it. PresenceBench evaluates how...
Annotrace measures agreement between any two annotators, human or AI, and reads six trace formats, including OpenTelemetry GenAI, LangSmith and Langfuse, and turns each run into an ordered, nested list of steps.
Arun Josephraj Arokiaraj, Chen Huang, Bin Wu et al.· 0 citations
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Large language model chatbots have been proposed as AI-interviewers for collecting qualitative interview data at scale, potentially bridging social science's longstanding divide between the breadth of surveys and the depth of qualitative interviews. This paper provides the first direct empirical comparison of data qual...
S. Güven, T. Gårdhus, Andreas Bjerre-Nielsen et al.· 0 citations
Misinformation harms public health and democracy, and generative artificial intelligence now writes falsehoods as persuasive as people's. Defences range from fact-checking individual claims to training people to resist falsehoods. Yet many claims are too new to check, and interventions that teach doubt can reduce belie...
Refusal is a common safety mechanism in large language models (LLMs), yet in contexts of suicidal ideation (SI), refusing to engage can itself constitute a safety failure. We evaluate how eight instruction-tuned LLMs respond to SI and self-harm disclosures across three datasets, varying whether models are informed that...
Drishti Goel, Soorya Ram Shimgekar, Jeongah Lee et al.· 0 citations
Computer-use agents (CUAs) are commonly evaluated against fixed task specifications, but users may omit requirements, add constraints, or require approval before consequential actions. Completing the benchmark instruction does not guarantee serving the person who asked. We introduce PersonaCUABench, which holds 74 task...
A conceptual framework linking data quality assurance, feature engineering, model training and reliability testing, and deployment to an agent population is proposed, closed by a cross-agent monitoring and feedback loop.
Harsh Verma· European journal of computer...· 0 citations
Cross-cutting political content is often expected to mitigate polarization, yet encounters across ideological lines do not necessarily foster more constructive engagement. We analyzed 4,584 posts from 1,243 Facebook pages sharing 761 political news links in a dataset centered on Brazil's 2018 presidential election, and...
Thiago Magrin, Jordan Kobellarz, Pedro O. S. Vaz-de-Melo et al.· 0 citations
As AI agents acquire names, avatars, phone numbers, and persistent personalities, they increasingly inhabit the same messaging platforms and group conversations as the humans they serve, crossing from tools their users operate into social entities their users relate to. Yet no existing framework identifies the infrastr...
Current human-AI interaction (HAI) only surfaces model outputs, hiding how LLM behavior can shift unpredictably toward unsafe behaviors in multi-turn conversations, potentially undermining users' goals or wellbeing. To address this harmful opacity in multi-turn HAI, we introduce an interface that surfaces an LLM's inte...
Sheer Karny, Anthony Baez, Pat Pataranutaporn· 0 citations
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…
Professor Paris Smaragdis develops computers with superhuman hearing for applications like speech recognition, music understanding, and environmental monitoring.
MIT News · Artificial Intelligence· news.mit.eduOct 23, 2026
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.”
MIT News · Artificial Intelligence· news.mit.eduOct 23, 2026
Assistant Professor Benjamin Lindquist studies how engineers deliberately injected randomness into early AI, giving rise to deep-learning models that sometimes hallucinate.
MIT News · Artificial Intelligence· news.mit.eduOct 22, 2026
“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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