activity
20242026
most citedWhat Are You Really Asking For? A Comparative 5W1H Analysis of Learner Questioning in CPR Training with IVAs in Screen-based and Augmented Reality Environments

2 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

cs.HC2026★ 2 cited

What Are You Really Asking For? A Comparative 5W1H Analysis of Learner Questioning in CPR Training with IVAs in Screen-based and Augmented Reality Environments

Hyerim Park, Jinseok Hong, Heejeong Ko +1

Question-asking is one of the key indicators of cognitive engagement. However, understanding how the distinct psychological affordances of presentation media shape learners' spoken…

cs.AI2026

Distilling Metacognitive Behaviors through Agentic Editing

Ik-hwan Kim, Hyeongrok Han, Mingi Jung +5

Distilling long reasoning traces from a teacher model into a smaller student also passes on the teacher's reasoning habits. Prior work and our annotation of teacher traces show tha…

cs.HC2025

Viewpoint-Tolerant Depth Perception for Shared Extended Space Experience on Wall-Sized Display

Dooyoung Kim, Jinseok Hong, Heejeong Ko +1

We proposed viewpoint-tolerant shared depth perception without individual tracking by leveraging human cognitive compensation in universally 3D rendered images on a wall-sized disp…

cs.CL2025

LLM Meets Scene Graph: Can Large Language Models Understand and Generate Scene Graphs? A Benchmark and Empirical Study

Dongil Yang, Minjin Kim, Sunghwan Kim +5

The remarkable reasoning and generalization capabilities of Large Language Models (LLMs) have paved the way for their expanding applications in embodied AI, robotics, and other rea…

cs.HC2024

Meta-Objects: Interactive and Multisensory Virtual Objects Learned from the Real World for Use in Augmented Reality

Dooyoung Kim, Taewook Ha, Jinseok Hong +4

We introduce the concept of a meta-object, a next-generation virtual object that inherits the form, properties, and functions of its real-world counterpart, enabling seamless synch…