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cs.HC2024

Datasets of Visualization for Machine Learning

Can Liu, Ruike Jiang, Shaocong Tan +4

Datasets of visualization play a crucial role in automating data-driven visualization pipelines, serving as the foundation for supervised model training and algorithm benchmarking.…

cs.HC2024

AutoLegend: A User Feedback-Driven Adaptive Legend Generator for Visualizations

Can Liu, Xiyao Mei, Zhibang Jiang +2

We propose AutoLegend to generate interactive visualization legends using online learning with user feedback. AutoLegend accurately extracts symbols and channels from visualization…

cs.HC2024

Breathing New Life into Existing Visualizations: A Natural Language-Driven Manipulation Framework

Can Liu, Jiacheng Yu, Yuhan Guo +3

We propose an approach to manipulate existing interactive visualizations to answer users' natural language queries. We analyze the natural language tasks and propose a design space…

cs.HC2024

A Spatial-Constraint Model for Manipulating Static Visualizations

Can Liu, Yu Zhang, Cong Wu +2

We propose a spatial-constraint approach for modeling spatial-based interactions and enabling interactive visualizations, which involves the manipulation of visualizations through…

cs.HC2024

PrompTHis: Visualizing the Process and Influence of Prompt Editing during Text-to-Image Creation

Yuhan Guo, Hanning Shao, Can Liu +2

Generative text-to-image models, which allow users to create appealing images through a text prompt, have seen a dramatic increase in popularity in recent years. However, most user…