I am a second-year M.S. student in the Department of Industrial and Systems Engineering at KAIST, advised by Prof. Hwanjun Song. I received my B.S. in Industrial Engineering from Yonsei University, where I worked as a research intern with Prof. Kyungwoo Song. I hold dual citizenship of the United States of America and the Republic of Korea, and I am planning to apply for Ph.D. programs in Fall 2026 as a domestic student in the U.S.
My research focuses on enhancing multimodal large language models (LLMs) and vision–language models (VLMs) for deeper understanding across multiple modalities, including images, text, audio, and video. I am particularly interested in advancing AI–human interaction, aiming to develop systems where AI can accurately interpret human intentions and humans can effectively guide AI’s development.
Publications
Robust Dataset Condensation using Supervised Contrastive Learning
Nicole Hee-Yeon Kim and Hwanjun Song
ICCV 2025, Main
[paper] [code]
Towards Multi-dimensional Evaluation of LLM Summarization across Domains and Languages
Hyangsuk Min, Yuho Lee, Minjeong Ban, Jiaqi Deng, Nicole Hee-Yeon Kim, Taewon Yun, Hang Su, Jason Cai, Hwanjun Song
ACL 2025, Main
[paper] [code]
IMC: A Benchmark for Invariant Learning under Multiple Causes
Taero Kim, Seonggyun Lee, Joonseong Kang, Youngjun Choi, Wonsang Yun, Nicole Hee-Yeon Kim, Ziyu Chen, Lexing Xie, Kyungwoo Song
CVPR 2025 Workshop on Domain Generalization: Evolution, Breakthroughs, and Future Horizons, Best Paper Award
[paper] [code]
Learning to Verify Summary Facts with Fine-Grained LLM Feedback
Jihwan Oh, Jeonghwan Choi, Nicole Hee-Yeon Kim, Taewon Yun, Hwanjun Song
COLING 2025, Oral
[paper] [code]
Robust Dataset Condensation via Semi-Supervised Learning
Nicole Hee-Yeon Kim, Jeonghwan Choi, Yuho Lee, Hwanjun Song
KCC 2025, Oral (in Korean)
Improving Language Model Quality through LLM-based Fine-Grained Hallucinated Summary Generation
Jihwan Oh, Jeonghwan Choi, Nicole Hee-Yeon Kim, Hwanjun Song
Journal of Computing Practice, vol. 31(2), pp. 91-97. (in Korean)
[paper]
Robust Dataset Condensation via Supervised Contrastive Learning
Nicole Hee-Yeon Kim, Jeonghwan Choi, Yuho Lee, Hwanjun Song
KSC 2024, Oral (in Korean)
[paper]
Improving the Text Summary Quality Through Understanding the Hallucination Level of Summarization Using Large Language Models
Jihwan Oh, Jeonghwan Choi, Nicole Hee-Yeon Kim, Hwanjun Song
KCC 2024, Oral (in Korean)
[paper]
Patent
Patent Pending – KAIST Patent Registration ID: KR P2025-0286, Robust Dataset Condensation using Supervised Contrastive Learning
Honors and Awards
- Best Paper Award — CVPR 2025 Workshop, 2025
- KAIST Support Scholarship (Government-funded full tuition scholarship for M.S. program), 2024–Present
- Brain Korea 21 (BK21) Scholarship (Government-funded research scholarship for graduate students), 2024–Present
- Korea Computer Congress Outstanding Presentation Paper Award, 2024
- Yonsei Welfare Scholarship (Full tuition scholarship for B.S. program), 2019–2023
- 1st Place, Department of Industrial Engineering Promotional Video Contest, 2022
- University Innovation Support Scholarship, 2020–2021
- Teaching Assistant Scholarship for the Data Science Program, 2020–2021
- Yonsei Social Entrepreneurship Award, 2021