1 citations · 1 across the 2 of their papers we have counts for
5 papers
Metacognitive Behavioral Tuning of Large Language Models for Multi-Hop Question Answering
Ik-hwan Kim, Hyeongrok Han, Mingi Jung +5
Large Language Models (LLMs) often produce incorrect answers on multi-hop question answering even when the reasoning trace already contains a correct intermediate conclusion. We at…
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…
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…
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…
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…