11 citations · 25 across the 7 of their papers we have counts for
7 papers
Chart-to-Experience: Benchmarking Multimodal LLMs for Predicting Experiential Impact of Charts
Seon Gyeom Kim, Jae Young Choi, Ryan Rossi +2
The field of Multimodal Large Language Models (MLLMs) has made remarkable progress in visual understanding tasks, presenting a vast opportunity to predict the perceptual and emotio…
Optimizing Data Delivery: Insights from User Preferences on Visuals, Tables, and Text
Reuben Luera, Ryan Rossi, Franck Dernoncourt +9
In this work, we research user preferences to see a chart, table, or text given a question asked by the user. This enables us to understand when it is best to show a chart, table,…
Understanding the Impact of Spatial Immersion in Web Data Stories
Seon Gyeom Kim, Juhyeong Park, Yutaek Song +6
An increasing number of web articles engage the reader with the feeling of being immersed in the data space. However, the exact characteristics of spatial immersion in the context…
An Evaluation-Focused Framework for Visualization Recommendation Algorithms
Zehua Zeng, Phoebe Moh, Fan Du +5
Although we have seen a proliferation of algorithms for recommending visualizations, these algorithms are rarely compared with one another, making it difficult to ascertain which a…
Insight-centric Visualization Recommendation
Camille Harris, Ryan A. Rossi, Sana Malik +5
Visualization recommendation systems simplify exploratory data analysis (EDA) and make understanding data more accessible to users of all skill levels by automatically generating v…
Personalized Visualization Recommendation
Xin Qian, Ryan A. Rossi, Fan Du +5
Visualization recommendation work has focused solely on scoring visualizations based on the underlying dataset and not the actual user and their past visualization feedback. These…