8 papers
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…
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…
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…
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…