collaborators

5 papers

cs.HC2026

Vibe Visualizing: How Visualization Novices Try (and Fail) to Generate and Interpret Visualizations with Conversational AI

Sam Yu-Te Lee, Yun-Hsin Kuo, Chifang Chou +3

Conversational AI has enabled users to generate and interpret visualizations through natural language, significantly lowering the technical barrier to entry. The increased accessib…

cs.DC2026

Understanding Large-Scale HPC System Behavior Through Cluster-Based Visual Analytics

Allison Austin, Shilpika, Yan To Linus Lam +4

In high-performance computing (HPC) environments, system monitoring data is often unlabeled and high-dimensional, making it difficult to reliably detect and understand anomalous co…

cs.HC2025

Navigating High-Dimensional Backstage: A Guide for Exploring Literature for the Reliable Use of Dimensionality Reduction

Hyeon Jeon, Hyunwook Lee, Yun-Hsin Kuo +6

Visual analytics using dimensionality reduction (DR) can easily be unreliable for various reasons, e.g., inherent distortions in representing the original data. The literature has…

cs.HC2025

SpreadLine: Visualizing Egocentric Dynamic Influence

Yun-Hsin Kuo, Dongyu Liu, Kwan-Liu Ma

Egocentric networks, often visualized as node-link diagrams, portray the complex relationship (link) dynamics between an entity (node) and others. However, common analytics tasks a…

cs.HC2025

Unveiling High-dimensional Backstage: A Survey for Reliable Visual Analytics with Dimensionality Reduction

Hyeon Jeon, Hyunwook Lee, Yun-Hsin Kuo +6

Dimensionality reduction (DR) techniques are essential for visually analyzing high-dimensional data. However, visual analytics using DR often face unreliability, stemming from fact…