98 citations · 476 across the 15 of their papers we have counts for
16 papers
AI Agents and the Future of VIS
Chen Zhu-Tian, Nam Wook Kim, Saeed Boorboor +4
Recent advances in agents (i.e., autonomous, goal-driven AI systems that iteratively observe, act, and learn from their environments) offer a fundamentally different approach from…
Enhancing XAI Interpretation through a Reverse Mapping from Insights to Visualizations
Aniket Nuthalapati, Nicholas Hinds, Brian Y. Lim +1
As AI systems become increasingly integrated into high-stakes domains, enabling users to accurately interpret model behavior is critical. While AI explanations can be provided, use…
FlowForge: Guiding the Creation of Multi-agent Workflows with Design Space Visualization as a Thinking Scaffold
Pan Hao, Dongyeop Kang, Nicholas Hinds +1
Multi-agent workflows have become an effective strategy for tackling complicated tasks by decomposing them into multiple sub-tasks and assigning them to specialized agents. However…
A Critical Analysis of the Usage of Dimensionality Reduction in Four Domains
Dylan Cashman, Mark Keller, Hyeon Jeon +2
Dimensionality reduction is used as an important tool for unraveling the complexities of high-dimensional datasets in many fields of science, such as cell biology, chemical informa…
GNN101: Visual Learning of Graph Neural Networks in Your Web Browser
Yilin Lu, Chongwei Chen, Yuxin Chen +3
Graph Neural Networks (GNNs) have achieved significant success across various applications. However, their complex structures and inner workings can be challenging for non-AI exper…
KNOWNET: Guided Health Information Seeking from LLMs via Knowledge Graph Integration
Youfu Yan, Yu Hou, Yongkang Xiao +2
The increasing reliance on Large Language Models (LLMs) for health information seeking can pose severe risks due to the potential for misinformation and the complexity of these top…
MARVisT: Authoring Glyph-based Visualization in Mobile Augmented Reality
Chen Zhu-Tian, Yijia Su, Yifang Wang +3
Recent advances in mobile augmented reality (AR) techniques have shed new light on personal visualization for their advantages of fitting visualization within personal routines, si…
Augmenting Static Visualizations with PapARVis Designer
Chen Zhu-Tian, Wai Tong, Qianwen Wang +2
This paper presents an authoring environment for augmenting static visualizations with virtual content in augmented reality. Augmenting static visualizations can leverage the best…
Beyond Generating Code: Evaluating GPT on a Data Visualization Course
Chen Zhu-Tian, Chenyang Zhang, Qianwen Wang +5
This paper presents an empirical evaluation of the performance of the Generative Pre-trained Transformer (GPT) model in Harvard's CS171 data visualization course. While previous st…
GNNLens: A Visual Analytics Approach for Prediction Error Diagnosis of Graph Neural Networks
Zhihua Jin, Yong Wang, Qianwen Wang +3
Graph Neural Networks (GNNs) aim to extend deep learning techniques to graph data and have achieved significant progress in graph analysis tasks (e.g., node classification) in rece…
Visual Analysis of Discrimination in Machine Learning
Qianwen Wang, Zhenhua Xu, Zhutian Chen +3
The growing use of automated decision-making in critical applications, such as crime prediction and college admission, has raised questions about fairness in machine learning. How…
HypoML: Visual Analysis for Hypothesis-based Evaluation of Machine Learning Models
Qianwen Wang, William Alexander, Jack Pegg +2
In this paper, we present a visual analytics tool for enabling hypothesis-based evaluation of machine learning (ML) models. We describe a novel ML-testing framework that combines t…
Narvis: Authoring Narrative Slideshows for Introducing Data Visualization Designs
Qianwen Wang, Zhen Li, Siwei Fu +2
Visual designs can be complex in modern data visualization systems, which poses special challenges for explaining them to the non-experts. However, few if any presentation tools ar…
Towards Automated Infographic Design: Deep Learning-based Auto-Extraction of Extensible Timeline
Chen Zhu-Tian, Yun Wang, Qianwen Wang +2
Designers need to consider not only perceptual effectiveness but also visual styles when creating an infographic. This process can be difficult and time consuming for professional…
DeepDrawing: A Deep Learning Approach to Graph Drawing
Yong Wang, Zhihua Jin, Qianwen Wang +3
Node-link diagrams are widely used to facilitate network explorations. However, when using a graph drawing technique to visualize networks, users often need to tune different algor…
ATMSeer: Increasing Transparency and Controllability in Automated Machine Learning
Qianwen Wang, Yao Ming, Zhihua Jin +5
To relieve the pain of manually selecting machine learning algorithms and tuning hyperparameters, automated machine learning (AutoML) methods have been developed to automatically s…