Kyungmin Lee

I am a PhD student at KAIST, advised by Jinwoo Shin. Before my graduate studies, I was a researcher at Agency for Defense Development, working on Defense AI technology. I received my B.S. degrees in Mathematics and Electrical Engineering at KAIST in 2019.

My research interests span probabilistic machine learning, generative modeling, representation learning and their applications.

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Research Publications
Collaborative Score Distillation for Consistent Visual Synthesis
Subin Kim*, Kyungmin Lee*, Junesuk Choi, Jongheon Jeong, Kihyuk Sohn, Jinwoo Shin
ICML Workshop on Structured Probabilistic Inference and Generative Modeling, 2023
Paper | Project page
S-CLIP: Semi-supervised Vision-Language Pre-training using Few Specialist Captions
Sangwoo Mo, Minkyu Kim, Kyungmin Lee, Jinwoo Shin
Bias-to-Text: Debiasing Unknown Visual Biases through Language Interpretation
Younghyun Kim*, Sangwoo Mo*, Minkyu Kim, Kyungmin Lee, Jaeho Lee, Jinwoo Shin
ICML Workshop on Spurious Correlations, Invariance and Stability, 2023
Paper | Code
STUNT: Few-shot Tabular Learning with Self-generated Tasks from Unlabeled Tables
Jaehyun Nam, Jihoon Tack, Kyungmin Lee, Hankook Lee, Jinwoo Shin
ICLR, 2023 (Spotlight Presentation)
NeurIPS Workshop on Table Representation Learning, 2022
Bronze Prize, Samsung Humantech Paper Awards, 2023
Paper | Openreview | Code

RényiCL: Contrastive Representation Learning with Skew Rényi divergence
Kyungmin Lee, Jinwoo Shin
NeurIPS, 2022
Paper | Openreview | Code
GCISG: Guided Causal Invariant Learning for Improved Syn-to-Real Generalization
Gilhyun Nam, Gyeongjae Choi, Kyungmin Lee
ECCV, 2022
Pseudo-spherical Knowledge Distillation
Kyungmin Lee, Hyeongkeun Lee
Representation Distillation by Prototypical Contrastive Predictive Coding
Kyungmin Lee
ICLR, 2022
NeurIPS Workshop on Self-supervised Learning: Theory and Practice, 2021
Paper | Openreview
Provable Defense by Denoised Smoothing with Learned Score function
Kyungmin Lee
ICLR Workshop on Security and Safety in Machine Learning Systems, 2021 (Travel Award)

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