Conference(* denotes the equal contribution. )

• [S1] Likelihood Ratio Aware Data Selection for Preference Learning

  • Under Review

  • Heesun Bae, Mina Kang, Sumin Lee, Byeonghu Na and Il-Chul Moon

• [C1] Missing Pattern Recognized Diffusion Imputation Model for Missing Not at Random

  • Under Review

  • Gyuwon Sim, Sumin Lee, HeeSun Bae, Byeonghu Na, Doyun Kwon, Ju-Hee Hwang, Jae-Young Lim, Il-chul Moon

• [C2] Semantic-aware Wasserstein Policy Regularization for Large Language Model Alignment

  • ICLR 2026 (The Fourteenth International Conference on Learning Representations)

  • Byeonghu Na, Hyungho Na, Yeongmin Kim, Suhyeon Jo, HeeSun Bae, Mina Kang, Il-chul Moon

• [C3] Preference Optimization by Estimating the Ratio of the Data Distribution

  • NeurIPS 2025 (The Thirty-ninth Annual Conference on Neural Information Processing Systems)

  • Yeongmin Kim, Heesun Bae, Byeonghu Na, Il-Chul Moon

• [C4] Diffusion Adaptive Text Embedding for Text-to-Image Diffusion Models

  • NeurIPS 2025 (The Thirty-ninth Annual Conference on Neural Information Processing Systems)

  • Byeonghu Na, Minsang Park, Gyuwon Sim, Donghyeok Shin, HeeSun Bae, Mina Kang, Se Jung Kwon, Wanmo Kang, Il-chul Moon

• [C5] Distilling Dataset into Neural Field

  • ICLR 2025 (The Thirteenth International Conference on Learning Representations)

  • Donghyeok Shin, HeeSun Bae, Gyuwon Sim, Wanmo Kang, Il-Chul Moon

• [S2] Dirichlet-based Per-Sample Weighting by Transition Matrix for Noisy Label Learning 

  • ICLR 2024 (The Twelfth International Conference on Learning Representations)

  • Heesun Bae, Seungjae Shin, Byeonghu Na and Il-Chul Moon

• • [C6] Unknown Domain Inconsistency Minimization for Domain Generalization

    • ICLR 2024 (The Twelfth International Conference on Learning Representations)

    • Seungjae Shin*, Heesun Bae*, Byeonghu Na, Yoon-yeong Kim, Il-Chul Moon

  • [C7] Label-Noise Robust Diffusion Models (International Conference on Learning Representation 

    • ICLR 2024 (The Twelfth International Conference on Learning Representations)

    • Byeonghu Na, Yeongmin Kim, HeeSun Bae, Jung Hyun Lee, Se Jung Kwon, Wanmo Kang, Il-Chul Moon

  • [C8] Make Prompts Adaptable: Bayesian Modeling for Vision-Language Prompt Learning with Data-Dependent Prior

    • AAAI 2024 (The 38th Annual AAAI Conference on Artificial Intelligence)

    • Youngjae Cho, HeeSun Bae, Seungjae Shin, YeoDong Youn, Weonyoung Joo, and Il-chul Moon

  • [C9] Loss Curvature Matching for Dataset Selection and Condensation 

    • AISTATS 2023 (The 26th International Conference on Artificial Intelligence and Statistics)

    • Seungjae Shin*, Heesun Bae*, DongHyeok Shin, Weonyoung Joo, Il-Chul Moon

  • [S3]  From Noisy Prediction to True Label: Noisy Prediction Calibration via Generative Model 

    • ICML 2022 (The Thirty-ninth International Conference on Machine Learning)

    • Heesun Bae*, Seungjae Shin*, Byeonghu Na, JoonHo Jang, Kyungwoo Song, Il-Chul Moon