Seon Gyeom Kim

Reuben Luera, Ryan Rossi, Franck Dernoncourt et al.

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, or text to the user for the specific question. For this, we conduct a user study where users are shown a question and asked what they would prefer to see and used the data to establish that a user's personal traits does influence the data outputs that they prefer. Understanding how user characteristics impact a user's preferences is critical to creating data tools with a better user experience. Additionally, we investigate to what degree an LLM can be used to replicate a user's preference with and without user preference data. Overall, these findings have significant implications pertaining to the development of data tools and the replication of human preferences using LLMs. Furthermore, this work demonstrates the potential use of LLMs to replicate user preference data which has major implications for future user modeling and personalization research.

Jaehoon Pyun, Younggeol Cho, Seon Gyeom Kim et al.

We propose an interaction technique called "Point & Select." It enables a driver to directly enter a point of interest (POI) into the in-vehicle infotainment system while driving in a city. Point & Select enables the driver to directly indicate with a finger, identify, adjust (if required), and finally confirm the POI on the screen by using buttons on the steering wheel. Based on a comparative evaluation of two conditions (driving-only and driving with input-task) on a simulator, we demonstrated the feasibility of the interaction in the driving context from the perspective of driver performance and interaction usability at speeds of 30, 50, and 70 km/h. Although the interaction usage and speed partially affected the driver's mental load, all the participants drove at an acceptable level in each condition. They carried out the task successfully with a success rate of 96.9% and task completion time of 1.82 seconds on average.