most citedComplexity-aware Large Scale Origin-Destination Network Generation via Diffusion Model

1 citations · 1 across the 6 of their papers we have counts for

collaborators

6 papers

cs.AI2024

Evaluating the Semantic Profiling Abilities of LLMs for Natural Language Utterances in Data Visualization

Hannah K. Bako, Arshnoor Bhutani, Xinyi Liu +2

Automatically generating data visualizations in response to human utterances on datasets necessitates a deep semantic understanding of the data utterance, including implicit and ex…

cs.CV2024

ASAP: Interpretable Analysis and Summarization of AI-generated Image Patterns at Scale

Jinbin Huang, Chen Chen, Aditi Mishra +3

Generative image models have emerged as a promising technology to produce realistic images. Despite potential benefits, concerns grow about its misuse, particularly in generating d…

cs.HC2023

WHATSNEXT: Guidance-enriched Exploratory Data Analysis with Interactive, Low-Code Notebooks

Chen Chen, Jane Hoffswell, Shunan Guo +5

Computational notebooks such as Jupyter are popular for exploratory data analysis and insight finding. Despite the module-based structure, notebooks visually appear as a single thr…

cs.HC2023

Mystique: Deconstructing SVG Charts for Layout Reuse

Chen Chen, Bongshin Lee, Yunhai Wang +2

To facilitate the reuse of existing charts, previous research has examined how to obtain a semantic understanding of a chart by deconstructing its visual representation into reusab…

cs.LG20231 cited

Complexity-aware Large Scale Origin-Destination Network Generation via Diffusion Model

Can Rong, Jingtao Ding, Zhicheng Liu +1

The Origin-Destination~(OD) networks provide an estimation of the flow of people from every region to others in the city, which is an important research topic in transportation, ur…

cs.HC2023

A Comparative Evaluation of Visual Summarization Techniques for Event Sequences

Kazi Tasnim Zinat, Jinhua Yang, Arjun Gandhi +2

Real-world event sequences are often complex and heterogeneous, making it difficult to create meaningful visualizations using simple data aggregation and visual encoding techniques…