WhatIf provides an interactive platform for real-time exploration of LLM-driven social simulations, enabling policymakers to iteratively test plans, reflect on assumptions, and uncover vulnerabilities in emergency preparedness scenarios.
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12 Pith papers cite this work. Polarity classification is still indexing.
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representative citing papers
Post-generation control in AI-assisted math visual creation yields higher teacher ratings for predictability and correctness than pre- or mid-generation control, with qualitative trade-offs in agency and effort.
Elemental Alchemist generates contextual tools and abstracts particle-system parameters into semantic mid-level attributes and high-level conceptual controls, with a user study indicating it helps practitioners translate creative goals into technical edits.
VRSafe adds false positive keystrokes to VR typing data to reduce keystroke inference attack accuracy and includes an efficient malicious login detector.
HolmeSketcher is a generative 3D sketching system for crime scene investigation that improves spatial accuracy and scene interpretability over 2D methods while increasing user task load.
A child-as-actor generative storytelling system updated by real-world food behavior increases preschoolers' willingness to try low-preference foods and reduces parental feeding pressure in a field study with 11 families.
Oversight strategy in computer-use agents shapes exposure to problematic actions more reliably than correction success, with plan-based approaches reducing occurrences but not uniformly improving interventions.
PrivacyMotiv generates LLM-created speculative personas and traceable journey stories to raise UX designers' empathy and motivation for privacy, yielding 59% more privacy issues found and 70% more redesign ideas in a study of 16 professionals.
A natural-language pipeline for authoring context-aware smart-home reminders was built and tested in two user studies (N=40, N=10) showing improved handling of complex conditions.
Industry markets AI agents for orchestration, creation, and insight, but a usability study with 31 participants reveals users face challenges from capability misalignment and lack of meta-cognition in tools like Operator and Manus.
SpatialBalancing is a system that turns revision trade-offs into spatial navigation so writers can iteratively balance scientific exposition and narrative engagement with LLM assistance.
An empirical study creates guidelines for interpreting the Human-Computer Trust Scale as a starting point for assessing trust propensity in technology interactions, while stressing the need for contextual reflection.
citing papers explorer
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WhatIf: Interactive Exploration of LLM-Powered Social Simulations for Policy Reasoning
WhatIf provides an interactive platform for real-time exploration of LLM-driven social simulations, enabling policymakers to iteratively test plans, reflect on assumptions, and uncover vulnerabilities in emergency preparedness scenarios.
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When Should Teachers Control AI Generation for Mathematics Visuals?
Post-generation control in AI-assisted math visual creation yields higher teacher ratings for predictability and correctness than pre- or mid-generation control, with qualitative trade-offs in agency and effort.
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Elemental Alchemist: A Generative Interface for Semantic Control of Particle Systems Across Dynamic Levels of Abstraction
Elemental Alchemist generates contextual tools and abstracts particle-system parameters into semantic mid-level attributes and high-level conceptual controls, with a user study indicating it helps practitioners translate creative goals into technical edits.
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VRSafe: A Secure Virtual Keyboard to Mitigate Keystroke Inference in Virtual Reality
VRSafe adds false positive keystrokes to VR typing data to reduce keystroke inference attack accuracy and includes an efficient malicious login detector.
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HolmeSketcher: Generative 3D Sketch Mapping for Spatial Reconstruction in Crime Scene Investigation
HolmeSketcher is a generative 3D sketching system for crime scene investigation that improves spatial accuracy and scene interpretability over 2D methods while increasing user task load.
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StoryEcho: A Generative Child-as-Actor Storytelling System for Picky-Eating Intervention
A child-as-actor generative storytelling system updated by real-world food behavior increases preschoolers' willingness to try low-preference foods and reduces parental feeding pressure in a field study with 11 families.
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Comparing Human Oversight Strategies for Computer-Use Agents
Oversight strategy in computer-use agents shapes exposure to problematic actions more reliably than correction success, with plan-based approaches reducing occurrences but not uniformly improving interventions.
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PrivacyMotiv: Speculative Persona Journeys for Empathic and Motivating Privacy Reviews in UX Design
PrivacyMotiv generates LLM-created speculative personas and traceable journey stories to raise UX designers' empathy and motivation for privacy, yielding 59% more privacy issues found and 70% more redesign ideas in a study of 16 professionals.
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Remind Me To Check The Stove Before I Leave The House: Authoring Personalized Context-Aware Smart Home Reminders Using Everyday Language
A natural-language pipeline for authoring context-aware smart-home reminders was built and tested in two user studies (N=40, N=10) showing improved handling of complex conditions.
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Why Johnny Can't Use Agents: Industry Aspirations vs. User Realities with AI Agents
Industry markets AI agents for orchestration, creation, and insight, but a usability study with 31 participants reveals users face challenges from capability misalignment and lack of meta-cognition in tools like Operator and Manus.
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Spatial Balancing: Harnessing Spatial Reasoning to Balance Scientific Exposition and Narrative Engagement in LLM-assisted Science Communication Writing
SpatialBalancing is a system that turns revision trade-offs into spatial navigation so writers can iteratively balance scientific exposition and narrative engagement with LLM assistance.
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How Much Trust is Enough? Towards Calibrating Trust in Technology
An empirical study creates guidelines for interpreting the Human-Computer Trust Scale as a starting point for assessing trust propensity in technology interactions, while stressing the need for contextual reflection.