SuperProvenanceWidgets adds cross-control provenance tracking to visualize how users interact with multiple UI elements over time, demonstrated through usage scenarios and a developer usability assessment.
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HiLSVA introduces a plan-first multi-agent LLM system for scientific visualization that incorporates explicit human oversight, stepwise provenance, and learn-at-test-time adaptation, evaluated via case studies and a 12-participant user study.
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SuperProvenanceWidgets: Tracking and Visualizing Analytic Provenance Across UI Control Elements
SuperProvenanceWidgets adds cross-control provenance tracking to visualize how users interact with multiple UI elements over time, demonstrated through usage scenarios and a developer usability assessment.
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HiLSVA: Design and Evaluation of a Human-in-the-Loop Agentic System for Scientific Visualization
HiLSVA introduces a plan-first multi-agent LLM system for scientific visualization that incorporates explicit human oversight, stepwise provenance, and learn-at-test-time adaptation, evaluated via case studies and a 12-participant user study.