Deep Barycentric Regression for Optimal Transport Map Estimation and its Statistical Optimality
· NeurIPS 2026
Kunwoong Kim, Insung Kong, Yongdai Kim
Spotlight Presentation (292/30709=0.95%)
Kunwoong Kim
Hi! I’m a postdoctoral researcher in KAIST AI, working with Jinwoo Shin. Before that, I completed my Ph.D. in Statistics at Seoul National University, advised by Yongdai Kim. My research brings together harnessing LLMs and AI agents efficiently and reliably, foundational questions in machine learning, and applications of AI across diverse domains, including science.
Publications
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DoG: Sniffing Out Overconfidence in LLM Agents via Post-hoc Trajectory Restructuring
· NeurIPS 2026
Hyunjun Jeon, Dongha Lim, Kunwoong Kim, Daewon Choi, Jinwoo Shin
Naive Visual Memory is Not Enough: A Failure-Mode Study of GUI Agents
· ICML 2026 workshop FAGEN (Failure Modes in Agentic AI)
Seoyoung Choi, Minseok Ko, Hyunseok Lee, Kunwoong Kim, Woomin Song, Chanseok Jeon, Jinwoo Shin
Doubly-Regressing Approach for Subgroup Fairness
· ICLR 2026
Kunwoong Kim*, Kyungseon Lee*, Jihu Lee, Dongyoon Yang, Yongdai Kim (*: co-first author)
Jihu Lee, Kunwoong Kim, Sehyun Park, Insung Kong, Dongyoon Yang, Yongdai Kim
Fair Model-based Clustering
· AAAI 2026
Jinwon Park, Kunwoong Kim, Jihu Lee, Yongdai Kim
Fair Clustering via Alignment
· ICML 2025
Kunwoong Kim, Jihu Lee, Sangchul Park, Yongdai Kim
Dongha Kim, Jaesung Hwang, Jongjin Lee, Kunwoong Kim, Yongdai Kim
IOFM: Using the Interpolation Technique on the Over-Fitted Models to Identify Clean-Annotated Samples
· AAAI 2024
Dongha Kim, Yongchan Choi, Kunwoong Kim, Ilsang Ohn, Yongdai Kim
Dongha Kim, Kunwoong Kim, Insung Kong, Ilsang Ohn, Yongdai Kim
No papers listed in this category yet.
ReLU Integral Probability Metric and its Applications
· Neural Networks 2026
Yuha Park, Kunwoong Kim, Insung Kong, Yongdai Kim
Fairness Through Matching
· Transactions on Machine Learning Research (TMLR) 2025
Kunwoong Kim, Insung Kong, Jongjin Lee, Minwoo Chae, Sangchul Park, Yongdai Kim
Fair Representation Learning for Continuous Sensitive Attributes using Expectation of Integral Probability Metrics
· IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2025
Insung Kong*, Kunwoong Kim*, Yongdai Kim (*: co-first author)
On Measuring the Quality of Group Fairness
· Journal of Artificial Intelligence Research and Applications 2024
Kunwoong Kim, Insung Kong, Jongjin Lee, Minwoo Chae, Sangchul Park, Yongdai Kim
Purifying Noisy Labels by Adversarial Search and SSL
· Journal of Artificial Intelligence Research and Applications 2024
Dongha Kim, Yongchan Choi, Kunwoong Kim, Yongdai Kim
Lq Regularization for Fair Artificial Intelligence Robust to Covariate Shift
· Statistical Analysis and Data Mining 2023
Seonghyeon Kim, Sara Kim, Kunwoong Kim, Yongdai Kim
SLIDE: A Surrogate Fairness Constraint to ensure Fairness Consistency
· Neural Networks 2022
Kunwoong Kim, Ilsang Ohn, Sara Kim, Yongdai Kim
No papers listed in this category yet.
What Drives the Inlier-Memorization Effect? A Theory of Outlier Detection via Early Training Dynamics
· Under review (2026+)
Kunwoong Kim, Dongha Kim
Approximating the Posterior Distribution of Bayesian Deep Neural Networks by a Deep Neural Network
· Under review (2026+)
Sehyun Park, Yunseop Shin, Kunwoong Kim, Jihu Lee, Yongdai Kim
Fair Bayesian Model-based Clustering
· Under review (2026+)
Jihu Lee*, Kunwoong Kim*, Hankyo Jeong, Yongdai Kim (*: co-first author)
Internal Fairness for Artificial Intelligence
· Under review (2026+)
Sehyun Park*, Kunwoong Kim*, Sara Kim, Kyusang Yu, Yongdai Kim (*: co-first author)
No papers listed in this category yet.
Academic Services
Area Chair: ICLR (2027~)
Conference Reviewer: NeurIPS, ICML, ICLR, AISTATS