My research focuses on Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Prompt Engineering, and Reasoning. I'm especially interested in chunking strategies, hallucination mitigation, and robust evaluation for LLM-based systems.
I also explore UX/UI for AI systems, aiming to design accessible and user‑friendly interfaces that connect theory with practice. My goal is to build trustworthy and human‑centered AI that bridges research and real-world impact.
Wonjun Jeong, Dongseok Kim, Taegkeun Whangbo
SCOPE: Stochastic and Counterbiased Option Placement for Evaluating Large Language Models
arXiv Preprint, 2025
Dongseok Kim, Wonjun Jeong, Gisung Oh
Convergence and Generalization of Anti-regularization for Parametric Models
arXiv Preprint, 2025
Dongseok Kim, Wonjun Jeong, Gisung Oh
Gaming and Cooperation in Federated Learning: What Can Happen and How to Monitor It
arXiv Preprint, 2025
Won-Jun Jeong, Gi-Sung Oh, Seok-Hee Oh, Taeg-Keun Whangbo
Establishment of Production Standards for Web‑based Metaverse Content: Focusing on Accessibility and HCI
Journal of Web Engineering, 2022
Yi‑Qian Han, Won-Jun Jeong, Gi‑Sung Oh, Seokhee Oh, Taeg‑Keun Whangbo
Using LDA Topic Modeling to Understand Regrowth Factors of the Chinese Gaming Industry in the COVID‑19 Era: Current Situation, Future and Predicament
Journal of Web Engineering, 2023