Safire is a two-dimensional conceptual model that defines visualization similarity via comparison criteria and representation modalities to support retrieval system design and analysis.
Data visualization practitioners’ perspectives on chartjunk
9 Pith papers cite this work. Polarity classification is still indexing.
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GFlowState introduces interactive visualizations such as trajectory node-link diagrams and transition heatmaps to make GFlowNet training dynamics observable for debugging and quality assessment.
BONSAI introduces a four-layer architecture and four-phase workflow for human-AI co-development of visual analytics applications, shown in case studies to enable efficient novel tool creation and reconstruction from paper descriptions.
Interviews with practitioners and educators yield a systematic account of annotation design considerations, trade-offs, and contextual judgments in visualization practice.
Teleoscope enables thematic curation of large Reddit corpora via interactive refinement, with three deployments indicating benefits in serendipitous keyword discovery, search saturation confidence, and collaborative curation discussions.
Linear theory predicts regimes for deformable surfaces in turbulence where the interface is enslaved by flow or shows intrinsic dynamics; simulations of air-water and rubber match predictions without wave turbulence.
Visualization researchers propose traceability—recording abundant annotated artifacts, reporting curated research threads, and enabling reading via interfaces—as a way to ensure rigor and transparency in inherently unreproducible design processes.
Context-mediated domain adaptation treats user modifications to AI artifacts as implicit domain specifications that reshape LLM-powered multi-agent reasoning, demonstrated via the Seedentia system which extracted 46 domain knowledge entries from expert edits.
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.
citing papers explorer
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Safire: Similarity Framework for Visualization Retrieval
Safire is a two-dimensional conceptual model that defines visualization similarity via comparison criteria and representation modalities to support retrieval system design and analysis.
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GFlowState: Visualizing the Training of Generative Flow Networks Beyond the Reward
GFlowState introduces interactive visualizations such as trajectory node-link diagrams and transition heatmaps to make GFlowNet training dynamics observable for debugging and quality assessment.
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BONSAI: A Mixed-Initiative Workspace for Human-AI Co-Development of Visual Analytics Applications
BONSAI introduces a four-layer architecture and four-phase workflow for human-AI co-development of visual analytics applications, shown in case studies to enable efficient novel tool creation and reconstruction from paper descriptions.
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Designing Annotations in Visualization: Considerations from Visualization Practitioners and Educators
Interviews with practitioners and educators yield a systematic account of annotation design considerations, trade-offs, and contextual judgments in visualization practice.
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Crystallizing Schemas with Teleoscope: Thematic Curation of Large Text Corpora on Reddit
Teleoscope enables thematic curation of large Reddit corpora via interactive refinement, with three deployments indicating benefits in serendipitous keyword discovery, search saturation confidence, and collaborative curation discussions.
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Free surfaces in turbulence -- A unified framework from water surfaces to elastic solids
Linear theory predicts regimes for deformable surfaces in turbulence where the interface is enslaved by flow or shows intrinsic dynamics; simulations of air-water and rubber match predictions without wave turbulence.
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Reflections on Traceability for Visualization Research
Visualization researchers propose traceability—recording abundant annotated artifacts, reporting curated research threads, and enabling reading via interfaces—as a way to ensure rigor and transparency in inherently unreproducible design processes.
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Context-Mediated Domain Adaptation in Multi-Agent Sensemaking Systems
Context-mediated domain adaptation treats user modifications to AI artifacts as implicit domain specifications that reshape LLM-powered multi-agent reasoning, demonstrated via the Seedentia system which extracted 46 domain knowledge entries from expert edits.
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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.