GUI agents can transform live web interfaces in real-time via DOM manipulations to deliver contextual assistance directly within the application.
Mixed citations
Title resolution pending
Mixed citation behavior. Most common role is background (62%).
13
Pith papers citing it
Background
62% of classified citations
citation-role summary
background 7
method 1
citation-polarity summary
representative citing papers
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.
Malleable Prompting reifies subjective preferences from natural language into GUI widgets and modulates LLM token probabilities during decoding to enable controllable generation, with a user study showing improved precision and perceived controllability over standard prompting.
Mixed-Initiative Context reconceptualizes interaction context as a dynamic, jointly manageable structure that humans and AI can actively organize according to task needs.
A qualitative study with 22 creative writers finds that the reflective value of AI refusals depends on alignment with users' situational thinking phases, cognitive beliefs, and views of AI roles.
Shorter LLM response latencies reduce perceived output thoughtfulness and usefulness, while task type affects prompting frequency independently of latency.
Adaptive Prompt Elicitation (APE) uses an information-theoretic framework to generate visual queries that elicit and compile user intent into better prompts for text-to-image models, showing improved alignment in benchmarks and a user study.
Chaplains view AI chatbots as unable to provide attuned pastoral care for non-clinical emotional needs, based on themes of listening, connecting, carrying, and wanting.
DataSway supports creation of semantically aligned animations for metaphoric data visualizations by generating clips via VLMs and coordinating timelines based on entity order, attributes, layout, or randomness.
Creatives prefer self-experimentation over structured guidance for GenAI image tools to preserve creative freedom, even when guidance aids AI literacy.
Pista decomposes AI agent actions in spreadsheets into auditable steps, enabling real-time user intervention that improves task outcomes, user comprehension, agent perception, and sense of co-ownership over baseline agents.
VIDEE introduces a human-in-the-loop system using Monte-Carlo Tree Search for task decomposition, executable pipeline generation, and LLM-based evaluation with visualizations to support non-expert text analytics.
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.
citing papers explorer
-
Beyond Chat and Clicks: GUI Agents for In-Situ Assistance via Live Interface Transformation
GUI agents can transform live web interfaces in real-time via DOM manipulations to deliver contextual assistance directly within the application.
-
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.
-
From Words to Widgets for Controllable LLM Generation
Malleable Prompting reifies subjective preferences from natural language into GUI widgets and modulates LLM token probabilities during decoding to enable controllable generation, with a user study showing improved precision and perceived controllability over standard prompting.
-
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.
-
Beyond Compliance: How AI Could Help Creative Writers by Refusing Them
A qualitative study with 22 creative writers finds that the reflective value of AI refusals depends on alignment with users' situational thinking phases, cognitive beliefs, and views of AI roles.
-
The Impact of Response Latency and Task Type on Human-LLM Interaction and Perception
Shorter LLM response latencies reduce perceived output thoughtfulness and usefulness, while task type affects prompting frequency independently of latency.
-
Adaptive Prompt Elicitation for Text-to-Image Generation
Adaptive Prompt Elicitation (APE) uses an information-theoretic framework to generate visual queries that elicit and compile user intent into better prompts for text-to-image models, showing improved alignment in benchmarks and a user study.
-
Chaplains' Reflections on the Design and Usage of AI for Conversational Care
Chaplains view AI chatbots as unable to provide attuned pastoral care for non-clinical emotional needs, based on themes of listening, connecting, carrying, and wanting.
-
DataSway: Vivifying Metaphoric Visualization with Animation Clip Generation and Coordination
DataSway supports creation of semantically aligned animations for metaphoric data visualizations by generating clips via VLMs and coordinating timelines based on entity order, attributes, layout, or randomness.
-
How Creatives Approach GenAI Image Generation: Tensions Between Structured Guidance, Self-Experimentation, and Creative Autonomy
Creatives prefer self-experimentation over structured guidance for GenAI image tools to preserve creative freedom, even when guidance aids AI literacy.
-
Auditing and Controlling AI Agent Actions in Spreadsheets
Pista decomposes AI agent actions in spreadsheets into auditable steps, enabling real-time user intervention that improves task outcomes, user comprehension, agent perception, and sense of co-ownership over baseline agents.
-
VIDEE: Visual and Interactive Decomposition, Execution, and Evaluation of Text Analytics with Intelligent Agents
VIDEE introduces a human-in-the-loop system using Monte-Carlo Tree Search for task decomposition, executable pipeline generation, and LLM-based evaluation with visualizations to support non-expert text analytics.
-
"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.