- 'Assigning Distinct Roles to Quantized and Low-Rank Matrices Toward Optimal Weight Decomposition' (ACL Findings)
- 'Understanding and Mitigating Memorization in Generative Models via Sharpness of Probability Landscapes' (ICML, Spotlight)
- 'Large Language Models Still Exhibit Bias in Long Text' (ACL Findings)
- 'An Information Theoretic Metric for Evaluating Unlearning Models' (Preprint)
Awards:
- 2nd place in CVPR CLVISION challenge
- 1st place in ICCV VCL challenge
Research Experience
Conducted research on Continual Learning in the context of computer vision; Gave a talk at Yonsei MLSys student group on Diffusion models & their privacy issues.
Education
Master's: Computer Science at Yonsei University, Advisor: Albert No
Background
First-year master's student in Computer Science at Yonsei University, focusing on safe and reliable AI, particularly generative models. Currently interested in advancing Diffusion Language Models (sampling methodologies and architectures) and developing efficient AI systems.