Jeongyeon Hwang

Jeongyeon Hwang

Jeongyeon Hwang

Hi! I’m Jeongyeon Hwang, a fourth year integrated M.S./Ph.D. candidate in the Graduate School of Artificial Intelligence at POSTECH, advised by Jungseul Ok.

My research focuses on improving the reliability of machine learning and natural language processing systems in real-world settings. In particular, I study large language models (LLMs), with an emphasis on robustness against adversarial inputs, corrupted training data, and potential misuse such as fake content generation. Recently, I have been especially interested in watermarking techniques for detecting LLM-generated text.

Please feel free to reach out via email at {firstname}.{lastname}@postech.ac.kr.

News

  • May 2026A paper (BIRA) got accepted at ICML 2026.
  • Jan 2026Received an Honorable Mention at the BK21 Outstanding Paper Awards from POSTECH GSAI.
  • Sep 2025Beginning a research visit at NYU (September–December).
  • Aug 2025Two papers (RA-RAG, LSC) got accepted at EMNLP 2025.
  • Aug 2024A paper (MedBN) got accepted at CVPR 2024.

Selected Publications

LLM Watermark Evasion via Bias Inversion

Jeongyeon Hwang, Sangdon Park, Jungseul Ok

ICML 2026

Paper

Retrieval-Augmented Generation with Estimation of Source Reliability

Jeongyeon Hwang, Junyoung Park, Hyejin Park, Sangdon Park, Jungseul Ok

EMNLP, 2025 Main (long)

Paper

Efficient Latent Semantic Clustering for Scaling Test-Time Computation of LLMs

Sungjae Lee, Hoyoung Kim, Jeongyeon Hwang, Eunhyeok Park, Jungseul Ok

EMNLP, 2025 Findings (long)

Paper

MedBN: Robust Test-Time Adaptation against Malicious Test Samples

Hyejin Park*, Jeongyeon Hwang*, Sunung Mun, Sangdon Park, Jungseul Ok

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024.

Paper