341 citations · 829 across the 33 of their papers we have counts for
11 papers · 1 filter
Data-Prompt Co-Evolution: Growing Test Sets to Refine LLM Behavior
Minjae Lee, Minsuk Kahng
Large Language Models (LLMs) are increasingly embedded in applications, and people can shape model behavior by editing prompt instructions. Yet encoding subtle, domain-specific pol…
The Evolution of LLM Adoption in Industry Data Curation Practices
Crystal Qian, Michael Xieyang Liu, Emily Reif +7
As large language models (LLMs) grow increasingly adept at processing unstructured text data, they offer new opportunities to enhance data curation workflows. This paper explores t…
From Perception to Decision: Assessing the Role of Chart Types Affordances in High-Level Decision Tasks
Yixuan Li, Emery D. Berger, Minsuk Kahng +1
Visualization design influences how people perceive data patterns, yet most research focuses on low-level analytic tasks, such as finding correlations. The extent to which these pe…
LLM Comparator: Visual Analytics for Side-by-Side Evaluation of Large Language Models
Minsuk Kahng, Ian Tenney, Mahima Pushkarna +7
Automatic side-by-side evaluation has emerged as a promising approach to evaluating the quality of responses from large language models (LLMs). However, analyzing the results from…
DendroMap: Visual Exploration of Large-Scale Image Datasets for Machine Learning with Treemaps
Donald Bertucci, Md Montaser Hamid, Yashwanthi Anand +4
In this paper, we present DendroMap, a novel approach to interactively exploring large-scale image datasets for machine learning (ML). ML practitioners often explore image datasets…
CNN Explainer: Learning Convolutional Neural Networks with Interactive Visualization
Zijie J. Wang, Robert Turko, Omar Shaikh +5
Deep learning's great success motivates many practitioners and students to learn about this exciting technology. However, it is often challenging for beginners to take their first…
CNN 101: Interactive Visual Learning for Convolutional Neural Networks
Zijie J. Wang, Robert Turko, Omar Shaikh +5
The success of deep learning solving previously-thought hard problems has inspired many non-experts to learn and understand this exciting technology. However, it is often challengi…
GAN Lab: Understanding Complex Deep Generative Models using Interactive Visual Experimentation
Minsuk Kahng, Nikhil Thorat, Duen Horng Chau +2
Recent success in deep learning has generated immense interest among practitioners and students, inspiring many to learn about this new technology. While visual and interactive app…
Visual Analytics in Deep Learning: An Interrogative Survey for the Next Frontiers
Fred Hohman, Minsuk Kahng, Robert Pienta +1
Deep learning has recently seen rapid development and received significant attention due to its state-of-the-art performance on previously-thought hard problems. However, because o…
ActiVis: Visual Exploration of Industry-Scale Deep Neural Network Models
Minsuk Kahng, Pierre Y. Andrews, Aditya Kalro +1
While deep learning models have achieved state-of-the-art accuracies for many prediction tasks, understanding these models remains a challenge. Despite the recent interest in devel…
Chronodes: Interactive Multi-focus Exploration of Event Sequences
Peter J Polack, Shang-Tse Chen, Minsuk Kahng +4
The advent of mobile health technologies presents new challenges that existing visualizations, interactive tools, and algorithms are not yet designed to support. In dealing with un…