37 citations · 69 across the 17 of their papers we have counts for
23 papers
Guidelines Are Not Rules: Characterizing Terminologies around Visualization Design Guidelines
Anna L. Chinni, Md Dilshadur Rahman, Bon Adriel Aseniero +6
A common expectation in visualization research is that outcomes recommend how researchers and practitioners take action or make design decisions. We often express these as "guideli…
How Do LLMs See Charts? A Comparative Study on High-Level Visualization Comprehension in Humans and LLMs
Hyotaek Jeon, Hyunwook Lee, Minjeong Shin +6
Designers often create visualizations to achieve specific high-level analytical or communication goals. These goals require people to extract complex and interconnected data patter…
Designing Annotations in Visualization: Considerations from Visualization Practitioners and Educators
Md Dilshadur Rahman, Devin Lange, Ghulam Jilani Quadri +1
Annotation is a central mechanism in visualization design that enables people to communicate key insights. Prior research has provided essential accounts of the visual forms annota…
Seeing Graphs Like Humans: Benchmarking Computational Measures and MLLMs for Similarity Assessment
Seokweon Jung, Jeongmin Rhee, Seoyoung Doh +3
Comparing graphs to identify similarities is a fundamental task in visual analytics of graph data. To support this, visual analytics systems frequently employ quantitative computat…
Redundant is Not Redundant: Automating Efficient Categorical Palette Design Unifying Color & Shape Encodings with CatPAW
Chin Tseng, Arran Zeyu Wang, Ghulam Jilani Quadri +1
Colors and shapes are commonly used to encode categories in multi-class scatterplots. Designers often combine the two channels to create redundant encodings, aiming to enhance clas…
Visual Stenography: Feature Recreation and Preservation in Sketches of Noisy Line Charts
Rifat Ara Proma, Michael Correll, Ghulam Jilani Quadri +1
Line charts surface many features in time series data, from trends to periodicity to peaks and valleys. However, not every potentially important feature in the data may correspond…