About Me
I am a Ph.D. candidate at Machine Learning and Intelligence Lab (MLILAB) in Korea Advanced Institute of Science and Technology (KAIST), advised by Prof.Eunho Yang.
My research broadly focuses on large language models, with particular interests in reinforcement learning with verifiable rewards and agentic reinforcement learning.
Publications
Work Experiences
I developed Raon-Speech-9B and Raon-SpeechChat-9B, contributing especially to model probing and evaluation. I also conducted research on agentic reinforcement learning and harnesses, and investigated MoE merging and pruning methods.
I published a paper titled 「LearnerVoice: A Dataset of Non-Native English Learners’ Spontaneous Speech」, accepted to INTERSPEECH 2024. Additionally, I filed two patents: “System for Learning English Speaking and Method Thereof” and “System for Diagnosing and Learning Pronunciation and Method Thereof”.
I spearheaded the planning, development, and deployment of an AI-driven engine, CAF, which predicts IELTS and TOEFL speaking scores by analyzing conversations between tutors and learners.
Projects
KRAFTON developed A.X K1 to integrate Non-thinking and Thinking modes into a single model, enabling either fast responses or deeper reasoning through a mode-specific chat template. We explored multiple data recipes and found paired training on the same prompts effective for making the model follow the think token rather than surface-level prompt cues. This recipe was incorporated into A.X K1 training.