Lookahead Sample Reward Guidance for Test-Time Scaling of Diffusion Models

Yeongmin Kim, Donghyeok Shin, Byeonghu Na, Minsang Park, Richard Lee Kim, and Il-Chul Moon , 2026 , Jul

Distillation of Large Language Models via Concrete Score Matching

Yeongmin Kim, Donghyeok Shin, Mina Kang, Byeonghu Na, and Il-Chul Moon , 2026 , International Conference on Learning Representations (ICLR 2026) , April 23-27 , Rio de Janeiro , Brazil

AC-Sampler: Accelerate and Correct Diffusion Sampling with Metropolis-Hastings Algorithm

Minsang Park, Gyuwon Sim, Hyungho Na, Jiseok Kwak, Sumin Lee, Richard Lee Kim, Donghyeok Shin, Byeonghu Na, Yeongmin Kim, Il-chul Moon , 2026 , International Conference on Learning Representations (ICLR 2026) , April 23-27 , Rio de Janeiro , Brazil

Semantic-aware Wasserstein Policy Regularization for Large Language Model Alignment

Byeonghu Na, Hyungho Na, Yeongmin Kim, Suhyeon Jo, HeeSun Bae, Mina Kang, and Il-Chul Moon , 2026 , International Conference on Learning Representations (ICLR 2026) , April 23-27 , Rio de Janeiro , Brazil

AMiD: Knowledge Distillation for LLMs with $\alpha$-mixture Assistant Distribution

Donghyeok Shin, Yeongmin Kim, Suhyeon Jo, Byeonghu Na, and Il-Chul Moon , 2026 , International Conference on Learning Representations (ICLR 2026) , April 23-27 , Rio de Janeiro , Brazil

Prompt-Based Safety Guidance Is Ineffective for Unlearned Text-to-Image Diffusion Models

Jiwoo Shin, Byeonghu Na, Mina Kang, Wonhyeok Choi, and Il-chul Moon , 2025 , NeurIPS 2025 Workshop on Generative and Protective AI for Content Creation , Dec 6 , San Diego , USA

Training-Free Safe Text Embedding Guidance for Text-to-Image Diffusion Models

Byeonghu Na, Mina Kang, Jiseok Kwak, Minsang Park, Jiwoo Shin, SeJoon Jun, Gayoung Lee, Jin-Hwa Kim, and Il-Chul Moon , 2025 , Neural Information Processing Systems (NeurIPS 2025) , Dec 2 , San Diego , USA

Diffusion Adaptive Text Embedding for Text-to-Image Diffusion Models

Byeonghu Na, Minsang Park, Gyuwon Sim, Donghyeok Shin, HeeSun Bae, Mina Kang, Se Jung Kwon, Wanmo Kang, and Il-Chul Moon , 2025 , Neural Information Processing Systems (NeurIPS 2025) , Dec 2 , San Diego , USA

Preference Optimization by Estimating the Ratio of the Data Distribution

Yeongmin Kim, Heesun Bae, Byeonghu Na, and Il-Chul Moon , 2005 , Neural Information Processing Systems (NeurIPS 2025) , Nov 30 , San Diego , USA

Simulation Analysis of Sensor Placement and Target Interaction in DEVS Formalism

Yeeun Park, Hyungho Na, and Il-Chul Moon , 2025 , Annual Modeling and Simulation Conference 2025 , May 26-29 , Madrid , Spain

Diffusion Bridge AutoEncoders for Unsupervised Representation Learning

Yeongmin Kim, Kwanghyeon Lee, Minsang Park, Byeonghu Na, and Il-Chul Moon , 2025 , International Conference on Learning Representations (ICLR 2025) , Apr 24-28 , Singapore , Singapore

Trajectory-Class-Aware Multi-Agent Reinforcement Learning

Hyungho Na, Kwanghyeon Lee, Sumin Lee, and Il-Chul Moon , 2025 , International Conference on Learning Representations (ICLR 2025) , Apr 24-28 , Singapore , Singapore

Distilling Dataset into Neural Field

Donghyeok Shin, HeeSun Bae, Gyuwon Sim, Wanmo Kang, and Il-Chul Moon , 2025 , International Conference on Learning Representations (ICLR 2025) , Apr 24-28 , Singapore , Singapore

DPO-Finetuned Large Multi-Modal Planner with Retrieval-Augmented Generation

Kwanghyeon Lee, Mina Kang, Hyungho Na, Heesun Bae, Byeonghu Na, Doyun Kwon, Seungjae Shin, Yeongmin Kim, Taewoo Kim, Seungmin Yun, Il-Chul Moon , 2024 , Multi-modal Foundation Model meets Embodied AI Workshop, ICML2024 , Jul 26 , Vienna , Austria

DEVS-Based Simulation Acceleration for AI Training: Unmanned Surface Vehicle Case

Juho Choi, Jang Won Bae, and Il-Chul Moon , 2024 , Winter Simulation Conference (WSC2024) , Dec 15-18 , Orlando , USA