A survey of 457 papers yields a six-dimensional design space for abstraction in interactive systems that reframes gulfs of execution and evaluation while articulating cognitive and design processes for bridging abstraction gaps.
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GraphTide augments text with animated progressive nested entity-relationship graphs to improve comprehension over traditional or static graph methods.
Intent Lenses infer capture-time user intent from photos via LLMs to create dynamic, reusable interactive objects that generate and organize structured visual notes for later sensemaking.
Mixed-Initiative Context reconceptualizes interaction context as a dynamic, jointly manageable structure that humans and AI can actively organize according to task needs.
OOPrompt reifies user intents into structured manipulable artifacts to enable modular and iterative prompting in LLM-based interactive systems.
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 qualitative study of mixed-ability teams identifies four types of interrelated failures and workarounds in information representation use, influenced by stigmas and social dynamics.
Omakase monitors project documents to infer timely queries and distills research reports into actionable suggestions that users rated significantly more useful than raw reports.
PSI uses a shared personal-context bus to publish state and write-back affordances, turning isolated AI-generated modules into synchronized, chat-accessible instruments.
citing papers explorer
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Making Abstraction Concrete: A Design Space and Interaction Model of Abstraction in Interactive Systems
A survey of 457 papers yields a six-dimensional design space for abstraction in interactive systems that reframes gulfs of execution and evaluation while articulating cognitive and design processes for bridging abstraction gaps.
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GraphTide: Augmenting Knowledge-Intensive Text with Progressive Nested Graph
GraphTide augments text with animated progressive nested entity-relationship graphs to improve comprehension over traditional or static graph methods.
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Intent Lenses: Inferring Capture-Time Intent to Transform Opportunistic Photo Captures into Structured Visual Notes
Intent Lenses infer capture-time user intent from photos via LLMs to create dynamic, reusable interactive objects that generate and organize structured visual notes for later sensemaking.
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Mixed-Initiative Context: Structuring and Managing Context for Human-AI Collaboration
Mixed-Initiative Context reconceptualizes interaction context as a dynamic, jointly manageable structure that humans and AI can actively organize according to task needs.
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OOPrompt: Reifying Intents into Structured Artifacts for Modular and Iterative Prompting
OOPrompt reifies user intents into structured manipulable artifacts to enable modular and iterative prompting in LLM-based interactive systems.
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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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"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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Omakase: proactive assistance with actionable suggestions for evolving scientific research projects
Omakase monitors project documents to infer timely queries and distills research reports into actionable suggestions that users rated significantly more useful than raw reports.
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PSI: Shared State as the Missing Layer for Coherent AI-Generated Instruments in Personal AI Agents
PSI uses a shared personal-context bus to publish state and write-back affordances, turning isolated AI-generated modules into synchronized, chat-accessible instruments.