MS-COOT uses co-optimal transport on hypergraph representations of Morse-Smale complexes to enable explicit region-to-region matching for identifying structural events such as splitting and merging.
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3 Pith papers cite this work. Polarity classification is still indexing.
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SciVisAgentSkills provides reusable agent skills that raise mean task scores on a 108-task SciVis benchmark when paired with Codex and Claude Code agents.
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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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.