I am a Ph.D. candidate in Artificial Intelligence at KAIST, where I am advised by Prof. Eunho Yang in the Machine Learning and Intelligence Lab. I expect to graduate in February 2027.

My research focuses on RL-based post-training for robust reasoning in language and multimodal models. I study self-verification, instruction-following robustness, and multimodal reasoning with discrete diffusion. Previously, I worked on text-guided image editing and generative-model manipulation, and completed research internships at Sony Research and NAVER Cloud.

Publications

EMNLP 2026 Findings

Reasoning Model is Stubborn: Diagnosing Instruction Overriding in Reasoning Models

Doohyuk Jang*, Yoonjeon Kim*, Chanjae Park, Hyun Ryu, Eunho Yang

ICML 2026

Verifying Meta-Awareness via Predictive Rewards in Reasoning Models

Yoonjeon Kim*, Doohyuk Jang*, Eunho Yang

CVPR 2025

Preserve or Modify? Context-Aware Evaluation for Balancing Preservation and Modification in Text-Guided Image Editing

Yoonjeon Kim*, Soohyun Ryu*, Yeonsung Jung, Hyunkoo Lee, Joowon Kim, June Yong Yang, Jaeryong Hwang, Eunho Yang

ICLR 2023

Learning Input-Agnostic Manipulation Directions in StyleGAN with Text Guidance

Yoonjeon Kim, Hyunsu Kim, Junho Kim, Yunjey Choi, Eunho Yang

Expert Systems with Applications

Sequential Targeting: A Continual Learning Approach for Data Imbalance in Text Classification

Joel Jang, Yoonjeon Kim, Kyoungho Choi, Sungho Suh

Preprints

Preprint

Efficient Reinforcement for Visual-Textual Thinking with Discrete Diffusion Model

Yoonjeon Kim, Yuhta Takida, Chieh-Hsin Lai, Eunho Yang, Yuki Mitsufuji

Work Experience

Sony Research

Research Intern · Tokyo, Japan

  • Developed RL post-training methods for multimodal discrete diffusion models, targeting visual-textual reasoning and visual question answering.
  • Worked with Yuhta Takida and Chieh-Hsin (Jesse) Lai on multimodal reasoning and reinforcement learning.

NAVER Cloud

Machine Learning Research Intern · Bundang, South Korea

  • Researched dynamic Neural Radiance Fields for monocular-video 3D reconstruction.
  • Investigated diffusion-based NeRF model distillation for efficient 3D scene representation and generation.

Selected Projects

2024–2027Optimization and Network Interpretation for Large-Scale Machine LearningKAIST · National Research Foundation of Korea
2024–2025Efficient Foundation Models on Intel SystemsKAIST / NAVER · Intel Corporation & NAVER
2021–2023Hyper-Scale AI Foundation ModelsKAIST / NAVER

Invited Talks

AI EXPO KOREA · KAIST AI Tech Seminar

Presenter · COEX, Seoul

Education

2023–2027Ph.D. Candidate in Artificial IntelligenceKAIST · Advisor: Eunho Yang
2021–2023M.S. in Artificial IntelligenceKAIST · Advisor: Eunho Yang
2017–2021B.S. in Applied StatisticsYonsei University · Full Scholarship

Service

Reviewer for ICML, NeurIPS, ICLR, and CVPR. For a complete record, download my CV.