Persona-driven workflow and interface improve automated and human-AI red-teaming of generative AI by incorporating diverse perspectives into adversarial prompt creation.
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A generative reconstruction algorithm turns video into editable text prompts, enabling text-driven reauthoring as shown in a creator study that identified use cases such as virtual reshooting and tensions around coherence and creative alignment.
Semantic Prompting enables LLMs to perform precise incremental narrative revisions by perceiving semantic interactions in spatial layouts, addressing misalignment gaps in existing methods.
Critical Inker scaffolds critical reflection during AI-assisted writing via Socratic questioning and visual logical-error feedback, reporting 91.2% argument overlap with ground truth and 87% validity accuracy in a pilot evaluation.
Two controlled experiments show multi-agent LLM configurations with both tutors and peers deliver higher learning gains and less homogeneous outputs than single-LLM tutoring in math problem-solving and essay writing.
citing papers explorer
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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.
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Rewriting Video: Text-Driven Reauthoring of Video Footage
A generative reconstruction algorithm turns video into editable text prompts, enabling text-driven reauthoring as shown in a creator study that identified use cases such as virtual reshooting and tensions around coherence and creative alignment.
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Semantic Prompting: Agentic Incremental Narrative Refinement through Spatial Semantic Interaction
Semantic Prompting enables LLMs to perform precise incremental narrative revisions by perceiving semantic interactions in spatial layouts, addressing misalignment gaps in existing methods.
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Critical Inker: Scaffolding Critical Thinking in AI-Assisted Writing Through Socratic Questioning
Critical Inker scaffolds critical reflection during AI-assisted writing via Socratic questioning and visual logical-error feedback, reporting 91.2% argument overlap with ground truth and 87% validity accuracy in a pilot evaluation.
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Beyond the AI Tutor: Social Learning with LLM Agents
Two controlled experiments show multi-agent LLM configurations with both tutors and peers deliver higher learning gains and less homogeneous outputs than single-LLM tutoring in math problem-solving and essay writing.