Publications
Publications
(*: Equal contribution, C: Conferences, P: Preprint, W: Workshop)
(*: Equal contribution, C: Conferences, P: Preprint, W: Workshop)
[P1] Preference Optimization by Estimating the Ratio of the Data Distribution [pdf]
Yeongmin Kim, Heesun Bae, Byeonghu Na, Il-Chul Moon
[C10] Autoregressive Distillation of Diffusion Transformers [pdf][code]
Yeongmin Kim, Sotiris Anagnostidis, Yuming Du, Edgar Schönfeld, Jonas K Kohler, Markos Georgopoulos, Albert Pumarola, Ali Thabet, Artsiom Sanakoyeu
Conference on Computer Vision and Pattern Recognition (CVPR 2025) - Oral (Top 0.7%)
[C9] FlexiDiT: Your Diffusion Transformer Can Easily Generate High-Quality Samples with Less Compute [pdf]
Sotiris Anagnostidis, Gregor Bachmann, Yeongmin Kim, Jonas K Kohler, Markos Georgopoulos, Artsiom Sanakoyeu, Yuming Du, Albert Pumarola, Ali Thabet, Edgar Schönfeld
Conference on Computer Vision and Pattern Recognition (CVPR 2025) - Highlight (Top 2.9%)
[C8] Diffusion Bridge AutoEncoders for Unsupervised Representation Learning [pdf][code]
Yeongmin Kim, Kwanghyeon Lee, Minsang Park, Byeonghu Na, Il-Chul Moon
International Conference on Learning Representations (ICLR 2025) - Spotlight (Top 5.1%)
[W2] DPO-Finetuned Large Multi-Modal Planner with Retrieval-Augmented Generation @ EgoPlan Challenge ICML 2024 [pdf]
Kwanghyeon Lee, Mina Kang, Hyungho Na, Heesun Bae, Byeonghu Na, Doyun Kwon, Seungjae Shin, Yeongmin Kim, Taewoo Kim, Seungmin Yun, and Il-Chul Moon
The Multi-modal Foundation Model meets Embodied AI Workshop @ ICML 2024
[C7] Reward-based Input Construction for Cross-document Relation Extraction [pdf][code]
Byeonghu Na*, Suhyeon Jo*, Yeongmin Kim, Il-Chul Moon
Annual Meeting of the Association for Computational Linguistics (ACL 2024) - Oral
[C6] Diffusion Rejection Sampling [pdf][code]
Byeonghu Na, Yeongmin Kim, Minsang Park, Donghyeok Shin, Wanmo Kang, Il-Chul Moon
International Conference on Machine Learning (ICML 2024)
Qualcomm Innovation Fellowship Korea 2024
[C5] Training Unbiased Diffusion Models From Biased Dataset [pdf][code]
Yeongmin Kim, Byeonghu Na, Minsang Park, JoonHo Jang, Dongjun Kim, Wanmo Kang, Il-Chul Moon
International Conference on Learning Representations (ICLR 2024)
[C4] Label-Noise Robust Diffusion Models [pdf][code]
Byeonghu Na, Yeongmin Kim, HeeSun Bae, Jung Hyun Lee, Se Jung Kwon, Wanmo Kang, Il-Chul Moon
International Conference on Learning Representations (ICLR 2024)
[C3] Refining Generative Process with Discriminator Guidance in Score-based Diffusion Models [pdf][code][media1][media2]
Dongjun Kim*, Yeongmin Kim*, Se Jung Kwon, Wanmo Kang, Il-Chul Moon
International Conference on Machine Learning (ICML 2023) - Oral (Top 2.3%)
[C2] SAAL: Sharpness-Aware Active Learning [pdf][code]
Yoon-Yeong Kim*, Youngjae Cho*, JoonHo Jang, Byeonghu Na, Yeongmin Kim, Kyungwoo Song, Wanmo Kang, Il-Chul Moon
International Conference on Machine Learning (ICML 2023)
[W1] Unsupervised Controllable Generation with Score-based Diffusion Models: Disentangled Latent Code Guidance [pdf]
Yeongmin Kim, Dongjun Kim, HyeonMin Lee, Il-Chul Moon
NeurIPS 2022 Workshop on Score-Based Methods
[C1] Predict Sequential Credit Card Delinquency with VaDE-Seq2Seq [pdf]
Yeongmin Kim, Youngjae Cho, Hanbit Lee, Il-Chul Moon
2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC)