Persona-driven workflow and interface improve automated and human-AI red-teaming of generative AI by incorporating diverse perspectives into adversarial prompt creation.
hub Mixed citations
As an AI language model, I cannot
Mixed citation behavior. Most common role is background (67%).
18
Pith papers citing it
90
external citations · external index
Background
67% of classified citations
hub tools
citation-role summary
background 12
citation-polarity summary
years
2026 18roles
background 11representative citing papers
Youth on Character.AI use chatbots for emotional restoration, creative exploration, and identity transformation, yielding a new three-intent framework and seven-archetype taxonomy from Discord discourse analysis.
AI-authored goals produce higher SMART quality scores but lower psychological ownership, commitment, importance, and goal-directed behavior than self-authored goals, with ownership as the mediating mechanism.
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.
Each tested LLM shows its own characteristic unreliability when engaging in repair during extended math-question dialogues.
A merged-token graph of many LM generations helps users compare output diversity, while raw lists remain better for detail-oriented distributional questions.
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.
Polite chatbot feedback lowers psychological reactance and boosts behavioral intentions but lacks engagement, whereas verbal leakage heightens surprise and engagement at the expense of increased reactance.
Explanation preferences for AI privacy redaction vary systematically with domain and redaction amount; giving users their preferred styles raises trust over random or no explanations.
Exploratory user study of 48 participants finds trade-offs in efficiency, contextual alignment, and social comfort when AI writing assistance varies along synchronous and visual dimensions.
AVA is a specialized GenAI platform for development policy research that provides verifiable syntheses from World Bank reports and is associated with 2.4-3.9 hours of weekly time savings in a large-scale user evaluation.
A collaborative VR workflow with GenAI lets users merge prompts and creatively repurpose outputs to co-create 3D artifacts that narrate shared cultural heritage experiences.
AI writing support reduces ownership most at drafting and least at planning, tracking how much text and ideas the AI contributes, while more AI help raises essay quality.
Exploratory lab study finds shared LLM use builds shared understanding in design teams while parallel use risks context drift, with professionals reflecting on outputs for insights but sometimes anchoring early.
State-of-the-art LLMs respond inconsistently to queries from protected-group personas, with some responses omitting key information that should be provided.
An online experiment finds that showing users an overview of an AI's values reduces reliance on AI suggestions during writing tasks.
Comparative study of VRChat Discord finds distinct engagement, response dynamics, and attitudes in human versus AI support channels.
citing papers explorer
-
PersonaTeaming: Supporting Persona-Driven Red-Teaming for Generative AI
Persona-driven workflow and interface improve automated and human-AI red-teaming of generative AI by incorporating diverse perspectives into adversarial prompt creation.
-
Restoration, Exploration and Transformation: How Youth Engage Character.AI Chatbots for Feels, Fun and Finding themselves
Youth on Character.AI use chatbots for emotional restoration, creative exploration, and identity transformation, yielding a new three-intent framework and seven-archetype taxonomy from Discord discourse analysis.
-
Optimized but Unowned: How AI-Authored Goals Undermine the Motivation They Are Meant to Drive
AI-authored goals produce higher SMART quality scores but lower psychological ownership, commitment, importance, and goal-directed behavior than self-authored goals, with ownership as the mediating mechanism.
-
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.
-
Talking to a Know-It-All GPT or a Second-Guesser Claude? How Repair reveals unreliable Multi-Turn Behavior in LLMs
Each tested LLM shows its own characteristic unreliability when engaging in repair during extended math-question dialogues.
-
Beyond One Output: Visualizing and Comparing Distributions of Language Model Generations
A merged-token graph of many LM generations helps users compare output diversity, while raw lists remain better for detail-oriented distributional questions.
-
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.
-
Polite But Boring? Trade-offs Between Engagement and Psychological Reactance to Chatbot Feedback Styles
Polite chatbot feedback lowers psychological reactance and boosts behavioral intentions but lacks engagement, whereas verbal leakage heightens surprise and engagement at the expense of increased reactance.
-
Exploring the Interaction of Explanation Styles, Context, and Trust of AI Privacy Redaction in AI-mediated Interactions
Explanation preferences for AI privacy redaction vary systematically with domain and redaction amount; giving users their preferred styles raises trust over random or no explanations.
-
"It Felt a Bit Eerie": Exploring Humanlike Interactions During Collaborative Writing with an Artificial Agent
Exploratory user study of 48 participants finds trade-offs in efficiency, contextual alignment, and social comfort when AI writing assistance varies along synchronous and visual dimensions.
-
Learning from AVA: Early Lessons from a Curated and Trustworthy Generative AI for Policy and Development Research
AVA is a specialized GenAI platform for development policy research that provides verifiable syntheses from World Bank reports and is associated with 2.4-3.9 hours of weekly time savings in a large-scale user evaluation.
-
"From remembering to shaping": Narrating Shared Experiences by Co-Designing Cultural Heritage Artifacts in Collaborative VR
A collaborative VR workflow with GenAI lets users merge prompts and creatively repurpose outputs to co-create 3D artifacts that narrate shared cultural heritage experiences.
-
From Planning to Revision: How AI Writing Support at Different Stages Alters Ownership
AI writing support reduces ownership most at drafting and least at planning, tracking how much text and ideas the AI contributes, while more AI help raises essay quality.
-
The Role of LLMs in Collaborative Software Design
Exploratory lab study finds shared LLM use builds shared understanding in design teams while parallel use risks context drift, with professionals reflecting on outputs for insights but sometimes anchoring early.
-
Discriminatory Compliance: How LLMs Answer Queries from Protected Groups
State-of-the-art LLMs respond inconsistently to queries from protected-group personas, with some responses omitting key information that should be provided.
-
Framing an AI with Values Reduces AI Reliance in AI-supported Writing Tasks
An online experiment finds that showing users an overview of an AI's values reduces reliance on AI suggestions during writing tasks.
-
Comparative Analysis of Human vs. AI-powered Support in VRChat Communities on Discord: User Engagement, Response Dynamics and Interaction Patterns
Comparative study of VRChat Discord finds distinct engagement, response dynamics, and attitudes in human versus AI support channels.
- From Words to Widgets for Controllable LLM Generation