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Presentations in this session
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Cost-Benefit Modeling of Interactive Visual Machine Learning Systems
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HiLSVA: Design and Evaluation of a Human-in-the-Loop Agentic System for Scientific Visualization
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Explainable Mapper: Charting LLM Embedding Spaces Using Perturbation-Based Exploration, Explanation, and Verification Agents
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RuleScope: Semantic-aware Authoring of Data Validation Rules
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DARE: An Explainable AI-visualization Framework for Ill-defined Decision Making
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Treadstone: A Communication Channel for Human-AI Collaborative Data Analysis
emoji_eventsHonorable Mention
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