Taehong Moon
AI Researcher
KRAFTON
josephmoon2019 [AT] gmail.com
About
I am a deep learning researcher at KRAFTON, specializing in generative models for gaming applications. Currently, I am developing a Co-playable Character (CPC), a novel type of in-game character designed to interact with users in real-time, going beyond traditional rule-based NPCs. My work focuses on enabling efficient inference for such interactive agents.
More broadly, my goal is to design multi-modal generative models optimized for real-world deployment. I am also exploring how generative modeling can be applied across diverse domains, including vision, language, and audio.
News
- 05.2025: Two papers, ResGen and How to Move Your Dragon, accepted to ICML 2025.
- 01.2025: R2F accepted to ICLR 2025 as a spotlight presentation.
- 05.2024: A Simple Early Exiting Framework for Accelerated Sampling in Diffusion Models accepted to ICML 2024.
- 11.2023: Joined KRAFTON AI as a Deep Learning Researcher.
- 06.2023 – 10.2023: Deep Learning Research Internship at Naver Cloud, participated in developing HyperCLOVA-X.
Publications
(*: Equal contribution)
Efficient Generative Modeling with Residual Vector Quantization-Based Tokens
Jaehyeon Kim*, Taehong Moon*, Keon Lee, Jaewoong Cho
International Conference on Machine Learning (ICML), 2025
How to Move Your Dragon: Text-to-Motion Synthesis for Large-Vocabulary Objects
Wonkwang Lee, Jongwon Jeong*, Taehong Moon*, Hyeon-Jong Kim, Jaehyeon Kim, Gunhee Kim, Byeong-Uk Lee
International Conference on Machine Learning (ICML), 2025
Rare-to-Frequent: Unlocking Compositional Generation Power of Diffusion Models on Rare Concepts with LLM Guidance
Dongmin Park, Sebin Kim, Taehong Moon, Minkyu Kim, Kangwook Lee, Jaewoong Cho
International Conference on Learning Representations (ICLR),2025
A Simple Early Exiting Framework for Accelerated Sampling in Diffusion Models
Taehong Moon, Moonseok Choi, Eunggu Yun, Jongmin Yoon, Gayoung Lee, Jaewoong Cho, Juho Lee
International Conference on Machine Learning (ICML), 2024
HyperCLOVA X Technical Report
HyperCLOVA X, a family of large language models (LLMs) tailored to the Korean language and culture
Early Exiting for Accelerated Inference in Diffusion Models
Taehong Moon, Moonseok Choi, Eunggu Yun, Jongmin Yoon, Gayoung Lee, Juho Lee
ICML Workshop on Structured Probabilistic Inference & Generative Modeling, 2023
Fine-tuning Diffusion Models with Limited Data
Taehong Moon, Moonseok Choi, Gayoung Lee, Jung-Woo Ha, Juho Lee
NeurIPS Workshop on Score-Based Methods, 2022
Efficient Generative Modeling with Residual Vector Quantization-Based Tokens
Jaehyeon Kim*, Taehong Moon*, Keon Lee, Jaewoong Cho
International Conference on Machine Learning (ICML), 2025
How to Move Your Dragon: Text-to-Motion Synthesis for Large-Vocabulary Objects
Wonkwang Lee, Jongwon Jeong*, Taehong Moon*, Hyeon-Jong Kim, Jaehyeon Kim, Gunhee Kim, Byeong-Uk Lee
International Conference on Machine Learning (ICML), 2025
Rare-to-Frequent: Unlocking Compositional Generation Power of Diffusion Models on Rare Concepts with LLM Guidance
Dongmin Park, Sebin Kim, Taehong Moon, Minkyu Kim, Kangwook Lee, Jaewoong Cho
International Conference on Learning Representations (ICLR),2025
A Simple Early Exiting Framework for Accelerated Sampling in Diffusion Models
Taehong Moon, Moonseok Choi, Eunggu Yun, Jongmin Yoon, Gayoung Lee, Jaewoong Cho, Juho Lee
International Conference on Machine Learning (ICML), 2024
HyperCLOVA X Technical Report
HyperCLOVA X, a family of large language models (LLMs) tailored to the Korean language and culture
Early Exiting for Accelerated Inference in Diffusion Models
Taehong Moon, Moonseok Choi, Eunggu Yun, Jongmin Yoon, Gayoung Lee, Juho Lee
ICML Workshop on Structured Probabilistic Inference & Generative Modeling, 2023
Fine-tuning Diffusion Models with Limited Data
Taehong Moon, Moonseok Choi, Gayoung Lee, Jung-Woo Ha, Juho Lee
NeurIPS Workshop on Score-Based Methods, 2022
Education
Korea Advanced Institute of Science and Technology (KAIST)
M.S. in Artificial IntelligenceSep. 2021 - Aug. 2023
Seoul National University (SNU)
B.S. in Industrial EngineeringMar. 2015 - Aug. 2021
Experience
KraftonNov. 2023 - Present
Deep Learning Research Engineer
Naver CloudJune. 2023 - Oct. 2023
Machine Learning Engineer Intern
HyperconnectJuly. 2020 - Aug. 2020
Machine Learning Research Intern
Seoul National University (SNU)Jan. 2020 - June. 2020
UROP program, hosted by Prof. U Kang
Academic Services
Conference Reviewer ICLR, NeurIPS
Workshop Reviewer SPIGM@ICML