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Hyemin Jeong
Hyemin Jeong
Welcome to my website! ☺️
I’m Hyemin Jeong, a master’s student at the Graduate School of Data Science, Seoul National University. I’m currently conducting research under the supervision of Prof. Joonseok Lee at Visual Information Processing Lab (VIP). My research interests include multimodal video understanding, safe LLMs, and hallucination reduction in multimodal LLMs.
Feel free to contact me through the links below. Here is my CV
Education
Education
Publication
Publication
K/DA: Automated Data Generation Pipeline for Detoxifying Implicitly Offensive Language in Korean Minkyeong Jeon*, Hyemin Jeong*, Yerang Kim, Jiyoung Kim, JaeHyeon Cho and Byung-Jun Lee Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics, 2025
Patent
Patent
Method for Detoxifying Implicitly Offensive Language in Korean using LLMsHyemin Jeong, Minkyeong Jeon, Yerang Kim, Jiyoung Kim, and Byung-Jun Lee (Patent under review)
Projects
Projects
Exploratory projects from my undergraduate studies, including independent experiments and toy implementations.
Sketch-Text based Image Retrieval for Fashion Products Jul 2024- Aug 2024 Github • Created a sketch-image paired dataset from fashion product images using edge maps and various post-processing techniques • Applied contrastive learning for sketch-text-image representation with CLIP
Outpainting with Edge Generation Mar 2024– Jun 2024 Github • Proposed a model architecture to enhance outpainting performance using Attention GAN and Repaint DDPM
DPO-based Korean Language Detoxification with Context-Appropriate EmojisMar 2024– Jun 2024 • Generated a 38k triplet(toxic-cleaned-cleaned with emojis) dataset in Korean using LLM • Utilized Direct Preference Optimization approach for language detoxiification
Improved Anticipate Accidents in Dashcam Videos Feb 2024– Apr 2024 Github • Enhanced the performance of the original paper by optimizing LSTM with a visual attention mechanism• Modified the model architecture and loss function to improve training stability
Fine-Tuning CLIP with Few-Shot Learning: Impact of Momentum on Performance Oct 2023– Dec 2023 Github • Improve the performance of few-shot learning in CLIP and deeply explored the impact of momentum in model performance
Language Skill
Language Skill
TEPS: 447 (Sep 2024)
TOEIC: 955 (Mar 2024)
OPIc: IM3 (Feb 2024)
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