LLMs routinely produce unsupported causal stories for personal sensing anomalies, and richer evidence or constrained prompts do not reliably eliminate this epistemic overreach.
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Predicting and explaining mobile ui tappability with vision modeling and saliency analysis
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Point&Grasp probabilistically integrates pointing and grasp gestures for out-of-reach object selection in MR, trained on a new ORG dataset, and outperforms single-cue baselines in user studies.
Presents a new retrieval system that enriches user queries with an intent taxonomy to improve matching of natural language descriptions to infographic designs and support authoring.
ShapeTalk coordinates an LLM-based natural-language parser and a sketch-based matcher for iterative, cross-modal time-series pattern search, translating free-form text into editable shape-feature constraints.
YouTube's recommendation algorithm prioritizes non-Kyrgyz content for Kyrgyz children, validating community concerns about cultural and linguistic erosion.
Co-design with five BLV experts produced a multi-modal prototype using reference sonification, stereo/volumetric audio, and buffer aggregation that co-designers said improved accuracy and learnability on tasks like peak finding and gradient tracing.
A 9-week mixed-methods study with 12 families found home displays significantly increased mood and goal tracking frequency over smartwatches alone, with multi-device setups accommodating diverse family routines and preferences.
GPT produces click distributions significantly different from real humans in 53% of UX first-click tasks, with prompting techniques like personas and chain-of-thought failing to improve alignment.
A new toolkit with cards and maps enables AI designers to juxtapose values and harms in early concept stages, shown valuable in designer surveys and interviews.
Designers using generative AI for concept envisioning engage in reciprocal reflection-in-action that surfaces multi-level value tensions and prioritizes harm recognition over positive value articulation.
NexusAI decomposes LLM inspirations into navigable functional fragments and abstractions to improve creative design space exploration, with a user study showing reduced cognitive overhead.
A six-month qualitative study of a mixed-ability nonprofit finds that conflicting access needs in communication act as a generative process revealing power structures and enabling accountability and repair rather than serving as technical problems to eliminate.
A qualitative study of mixed-ability teams identifies four types of interrelated failures and workarounds in information representation use, influenced by stigmas and social dynamics.
Smart glasses expand independent visual access for BLV participants in mixed-vision groups, supporting inclusive collaboration while sighted participants express uncertainty about adapting their helping behaviors.
citing papers explorer
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Causal Stories from Sensor Traces: Auditing Epistemic Overreach in LLM-Generated Personal Sensing Explanations
LLMs routinely produce unsupported causal stories for personal sensing anomalies, and richer evidence or constrained prompts do not reliably eliminate this epistemic overreach.
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Point & Grasp: Flexible Selection of Out-of-Reach Objects Through Probabilistic Cue Integration
Point&Grasp probabilistically integrates pointing and grasp gestures for out-of-reach object selection in MR, trained on a new ORG dataset, and outperforms single-cue baselines in user studies.
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Show Me the Infographic I Imagine: Intent-Aware Infographic Retrieval for Authoring Support
Presents a new retrieval system that enriches user queries with an intent taxonomy to improve matching of natural language descriptions to infographic designs and support authoring.
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ShapeTalk: Combining Natural Language and Sketch for Time-Series Pattern Querying
ShapeTalk coordinates an LLM-based natural-language parser and a sketch-based matcher for iterative, cross-modal time-series pattern search, translating free-form text into editable shape-feature constraints.
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Empire Amplifier: Uncovering and Contesting the Prioritization of Colonial Content on Platforms Through Community-Informed Algorithmic Auditing
YouTube's recommendation algorithm prioritizes non-Kyrgyz content for Kyrgyz children, validating community concerns about cultural and linguistic erosion.
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Three Modalities, Two Design Probes, One Prototype, and No Vision: Experience-Based Co-Design of a Multi-modal 3D Data Visualization Tool
Co-design with five BLV experts produced a multi-modal prototype using reference sonification, stereo/volumetric audio, and buffer aggregation that co-designers said improved accuracy and learnability on tasks like peak finding and gradient tracing.
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Evaluating Glanceable Multi-Device Family Health Tracking with Smartwatches and Home Displays
A 9-week mixed-methods study with 12 families found home displays significantly increased mood and goal tracking frequency over smartwatches alone, with multi-device setups accommodating diverse family routines and preferences.
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What Would GPT Click: Practical Effects of Human-AI Behavioral Misalignment and the Cost of Synthetic Participants in User Experience
GPT produces click distributions significantly different from real humans in 53% of UX first-click tasks, with prompting techniques like personas and chain-of-thought failing to improve alignment.
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Developing an AI Concept Envisioning Toolkit to Support Reflective Juxtaposition of Values and Harms
A new toolkit with cards and maps enables AI designers to juxtapose values and harms in early concept stages, shown valuable in designer surveys and interviews.
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How Designers Envision Value-Oriented AI Design Concepts with Generative AI
Designers using generative AI for concept envisioning engage in reciprocal reflection-in-action that surfaces multi-level value tensions and prioritizes harm recognition over positive value articulation.
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NexusAI: Enabling Design Space Exploration of Ideas through Cognitive Abstraction and Functional Decomposition
NexusAI decomposes LLM inspirations into navigable functional fragments and abstractions to improve creative design space exploration, with a user study showing reduced cognitive overhead.
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Designing for Collective Access: In Search of a Solution to Accessible Communication in a Mixed-Ability Non-Profit
A six-month qualitative study of a mixed-ability nonprofit finds that conflicting access needs in communication act as a generative process revealing power structures and enabling accountability and repair rather than serving as technical problems to eliminate.
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"If We Had the Information That We Need to Interpret the World Around Us, We Wouldn't Be Disabled:" Barriers and Opportunities in Information Work among Blind and Sighted Colleagues
A qualitative study of mixed-ability teams identifies four types of interrelated failures and workarounds in information representation use, influenced by stigmas and social dynamics.
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Reshaping Inclusive Interpersonal Dynamics through Smart Glasses in Mixed-Vision Social Activities
Smart glasses expand independent visual access for BLV participants in mixed-vision groups, supporting inclusive collaboration while sighted participants express uncertainty about adapting their helping behaviors.