4 papers
Evaluating Visual Prompts with Eye-Tracking Data for MLLM-Based Human Activity Recognition
Jae Young Choi, Seon Gyeom Kim, Hyungjun Yoon +7
Large Language Models (LLMs) have emerged as foundation models for IoT applications such as human activity recognition (HAR). However, directly applying high-frequency and multi-di…
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…
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…
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,…