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20242026
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cs.HC2026

A Typology of Decision-Making Tasks for Visualization

Camelia D. Brumar, Sam Molnar, Gabriel Appleby +2

Despite decision-making being a vital goal of data visualization, little work has been done to differentiate decision-making tasks within the field. While visualization task taxono…

cs.HC2025

Mitigating LLM Hallucinations with Knowledge Graphs: A Case Study

Harry Li, Gabriel Appleby, Kenneth Alperin +2

High-stakes domains like cyber operations need responsible and trustworthy AI methods. While large language models (LLMs) are becoming increasingly popular in these domains, they s…

cs.HC2025

Are Metrics Enough? Guidelines for Communicating and Visualizing Predictive Models to Subject Matter Experts

Ashley Suh, Gabriel Appleby, Erik W. Anderson +3

Presenting a predictive model's performance is a communication bottleneck that threatens collaborations between data scientists and subject matter experts. Accuracy and error metri…

cs.HC2024

Knowledge Graphs in Practice: Characterizing their Users, Challenges, and Visualization Opportunities

Harry Li, Gabriel Appleby, Camelia Daniela Brumar +2

This study presents insights from interviews with nineteen Knowledge Graph (KG) practitioners who work in both enterprise and academic settings on a wide variety of use cases. Thro…

cs.HC2024

DimBridge: Interactive Explanation of Visual Patterns in Dimensionality Reductions with Predicate Logic

Brian Montambault, Gabriel Appleby, Jen Rogers +3

Dimensionality reduction techniques are widely used for visualizing high-dimensional data. However, support for interpreting patterns of dimension reduction results in the context…

cs.HC2024

A Preliminary Roadmap for LLMs as Assistants in Exploring, Analyzing, and Visualizing Knowledge Graphs

Harry Li, Gabriel Appleby, Ashley Suh

We present a mixed-methods study to explore how large language models (LLMs) can assist users in the visual exploration and analysis of knowledge graphs (KGs). We surveyed and inte…