(Statistically/Theoretically) Principled Approaches to LLM Reasoning
Adaptive Appraoches to Improving Sample Efficiency of LLM Reasoning
TBD
- My Adobe internship
AdaSTaR: Adaptive Data Sampling for Training Self-Taught Reasoners
- arXiv preprint arXiv:2505.16322
- Led by Woosung Koh (Yonsei Univ.) along with Wonbeen Oh, Jaein Jang, MinHyung Lee, Hyeongjin Kim, Ah Yeon Kim (Yonsei Univ.). Also joint work with Joonkee Kim & Taehyeon Kim (LG AI Research) and Se-Young Yun (KAIST AI).
Junghyun Lee
PhD Student
PhD student at GSAI, KAIST, jointly advised by Profs. Se-Young Yun and Chulhee Yun. Research focuses on interactive machine learning, particularly at the intersection of RLHF and preference learning, and statistical analyses of large networks, with an emphasis on community detection. Broadly interested in mathematical and theoretical AI and related problems in mathematics.