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cs.HC2026

A Scoping Review of Mixed Initiative Visual Analytics in the Automation Renaissance

Shayan Monadjemi, Yuhan Guo, Kai Xu +2

Artificial agents are increasingly integrated into data analysis workflows, carrying out tasks that were primarily done by humans. Our research explores how the introduction of aut…

cs.HC2024

VAE Explainer: Supplement Learning Variational Autoencoders with Interactive Visualization

Donald Bertucci, Alex Endert

Variational Autoencoders are widespread in Machine Learning, but are typically explained with dense math notation or static code examples. This paper presents VAE Explainer, an int…

cs.HC2024

MiMICRI: Towards Domain-centered Counterfactual Explanations of Cardiovascular Image Classification Models

Grace Guo, Lifu Deng, Animesh Tandon +2

The recent prevalence of publicly accessible, large medical imaging datasets has led to a proliferation of artificial intelligence (AI) models for cardiovascular image classificati…

cs.HC2024

What We Augment When We Augment Visualizations: A Design Elicitation Study of How We Visually Express Data Relationships

Grace Guo, John Stasko, Alex Endert

Visual augmentations are commonly added to charts and graphs in order to convey richer and more nuanced information about relationships in the data. However, many design spaces pro…

cs.HC2024

Visualizing Intelligent Tutor Interactions for Responsive Pedagogy

Grace Guo, Aishwarya Mudgal Sunil Kumar, Adit Gupta +3

Intelligent tutoring systems leverage AI models of expert learning and student knowledge to deliver personalized tutoring to students. While these intelligent tutors have demonstra…