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human-computer interaction

2,089 papers

#artificial intelligence Preprint Sep 2026

The Evolution of Coordination in a Collective Intelligence System: 25 Years of English Wikipedia and the Emergence of Generative AI

English Wikipedia is one of the largest examples of collective intelligence on the Web, sustained not only by article production but also by volunteer coordination and governance. While prior research has examined coordination work in Wikipedia, less attention has been paid to how participation in these spaces has evol...

Neal Reeves, Maja Świeczkowska, Amy Rechkemmer et al. · 0 citations
#human-computer interacti... Preprint Sep 2026

EgoAsk: Egocentric Teaching of Personalized Object Knowledge for Household Robots

EgoAsk is introduced, a smart-glasses-based system that proactively embeds personalized object teaching into everyday activities and identifies gaps in personalized object knowledge, and analyzes ongoing activity to ask context-relevant questions that support future household assistance.

Yuan-Da Hu, Wen-Bin Zuo, Yi-Ting Shen et al. · 0 citations
#human-computer interacti... Preprint Sep 2026

NephoCodex: Exploring Bounded Material Agency in Weather Data Physicalization

NephoCodex, a data physicalization system informed by a formative study that constructs five artistic weather states and predicts probability distributions over them, is presented, showing how variable material expression can be paired with stable digital annotations and how embodied experience can be evaluated separat...

Yuxuan Weng, Yun-Ge Wen · 0 citations
#human-computer interacti... Preprint Sep 2026

CATVis: A Collaborative Multi-Agent Workflow for Turbomachinery Simulation Data Visualization

CATVis is presented, a Collaborative multi-agent workflow system that bridges the gap by transforming NL intents into structured middle representation for visualization, and significantly improves complex workflow generation correctness while reducing prompt complexity.

Zhe Wang, Zehao Lou, Guang-Hui Zhao et al. · 0 citations
#human-computer interacti... Preprint Sep 2026

EmoPhone: A Multi-Wave Dataset for In-the-Wild Mobile and Wearable Affect Sensing

These findings indicate that robust mobile affective computing is constrained not only by label availability but also by substantial participant-level variability and realistic cross-wave differences inherent in longitudinal in-situ deployments.

Pan-Yu Zhang, Minseo Park, Soowon Kang et al. · 0 citations
#human-computer interacti... Preprint Open access Sep 2026

Ptolemy: A Semantic Map of Exploratory Data Analysis

A central challenge in exploratory data analysis (EDA) is keeping track of what has already been examined in order to decide what to analyze next. In practice, analysts often run dozens of analyses while building an understanding of a dataset. However, most tools provide little support for maintaining an overview of th...

Dylan Wootton, Denny Bromley, Vidya Setlur · 0 citations
#robotics Preprint Sep 2026

Beyond Gestures: Estimating Full Hand Pose and Contact Forces from Wrist-Worn Pressure Sensor Array

A wrist-worn pressure-sensing wristband that recovers continuous full-hand pose and distributed contact force on a single wearable is introduced, and the key insight is that muscle contraction and tendon displacement produce pressure patterns, which correlate strongly with hand pose and interaction force.

S. Kolev, Ling-Ni Ma, Michael Goesele et al. · 0 citations
#human-computer interacti... Preprint Sep 2026

"ChatGPT, what am I missing?": Designing AI Workflows around Professional Task Structure to Shape Analytic AI Use

This work designed two scaffolded interfaces around the same negotiation scaffold: one presented a completed AI analysis, while the other supported user-directed, incremental development, which elicited a broader repertoire of analytic requests and lower subjective effort.

Zi-Lin Ma, Suzi Jazmati, Marco Chimenton et al. · 0 citations
#human-computer interacti... Preprint Open access Sep 2026

A light-touch AI literacy intervention helps protect against AI political persuasion

Conversations with large language models (LLMs) can substantially shift beliefs and attitudes, raising concerns about manipulation using AI persuasion. Here we test whether a light-touch AI literacy intervention - a brief warning that LLMs can be prompted to persuade and may present information selectively - helps prot...

Reed Orchinik, David Rand · 0 citations
#human-computer interacti... Preprint Sep 2026

Context-Aware Emotionally Adaptive Voice Assistants: A Multimodal Framework for Empathetic Human-Agent Interaction

Voice-assistant interruptions tend to be intrusive because existing systems fail to consider the affective state, cognitive load and situational context of the user when deciding when and how to interrupt.Voice-assistant interruptions tend to be intrusive, since existing systems do not consider the affective state, cog...

Tapon Kumer Ray, Rajkumar Yesuraj · 0 citations

From tech blogs

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Microsoft Research Blog Nov 5, 2026

Formally verifying agent-written full-stack web apps with PDD Kit

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…

MIT News · Artificial Intelligence Oct 28, 2026

Making machines that can listen

Professor Paris Smaragdis develops computers with superhuman hearing for applications like speech recognition, music understanding, and environmental monitoring.

MIT News · Artificial Intelligence Oct 23, 2026

Reinforcing the value of human understanding at MIT

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 Oct 23, 2026

Q&A: How AI came to model the “messy” human mind

Assistant Professor Benjamin Lindquist studies how engineers deliberately injected randomness into early AI, giving rise to deep-learning models that sometimes hallucinate.

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