Hyuk Kwon

I am a Ph.D. student at Yonsei University Machine Learning Lab, under the guidance of Prof. Kibok Lee. My research focuses on how visual models learn and adapt across diverse tasks and settings, and how to evaluate their performance and reliability. Since real-world data rarely matches what a model was trained on, I am especially interested in how models handle this gap and how we can tell whether they will still work. Recently, my interests have expanded to world models and physical AI.

Research interests: Open-world learning · Vision-language models · (Automatic) model evaluation · World models · Physical AI

📰 News

💼 Work Experience

Research Intern, Ludo Robotics (Seoul)
Sep 2026 – Present

📝 Publications

* equal contribution

Good Rankings, Poor Choices? Rethinking Language-Only Vision-Language Model Selection
Hyuk Kwon, Jaebyeong Jeon, Hyeonseo Jang, Kibok Lee
Preprint
arXiv
Enhancing Continual Learning of Vision-Language Models via Dynamic Prefix Weighting
Hyeonseo Jang, Hyuk Kwon, Kibok Lee
CVPR 2026
arXiv
Automated Model Evaluation for Object Detection via Prediction Consistency and Reliability
Seungju Yoo, Hyuk Kwon, Joong-Won Hwang, Kibok Lee
ICCV 2025 (Oral) Best Paper Award Candidate
arXiv
Rethinking Open-World Semi-Supervised Learning: Distribution Mismatch and Inductive Inference
Seongheon Park*, Hyuk Kwon*, Kwanghoon Sohn, Kibok Lee
CVPR Workshops 2024
arXiv

🎓 Education

Integrated M.S./Ph.D. student, Department of Statistics and Data Science, Yonsei University
2022 – Present
B.S., Department of Applied Statistics, Yonsei University
2016 – 2022