Preservation of the Global Knowledge by Not-True Self Knowledge Distillation in Federated Learning. - Gihun Lee; Yongjin Shin; Minchan Jeong; Se-Young Yun (CoRR, 2021)

Robust Streaming PCA. - Daniel Bienstock; Minchan Jeong; Apurv Shukla 001; Se-Young Yun (NeurIPS, 2022)

Preservation of the Global Knowledge by Not-True Distillation in Federated Learning. - Gihun Lee; Minchan Jeong; Yongjin Shin; Sangmin Bae; Se-Young Yun (NeurIPS, 2022)

Contextual Linear Bandits under Noisy Features: Towards Bayesian Oracles. - Jung-Hun Kim; Se-Young Yun; Minchan Jeong; Junhyun Nam; Jinwoo Shin; Richard Combes (AISTATS, 2023)

Toward Risk-based Optimistic Exploration for Cooperative Multi-Agent Reinforcement Learning. - Jihwan Oh; Joonkee Kim; Minchan Jeong; Se-Young Yun (AAMAS, 2023)

Revisiting Intermediate Layer Distillation for Compressing Language Models: An Overfitting Perspective. - Jongwoo Ko; Seungjoon Park; Minchan Jeong; Sukjin Hong; Euijai Ahn; Du-Seong Chang; Se-Young Yun (EACL (Findings), 2023)

Bayesian Multi-Task Transfer Learning for Soft Prompt Tuning. - Haeju Lee; Minchan Jeong; Se-Young Yun; Kee-Eung Kim (EMNLP (Findings), 2023)

FedSoL: Bridging Global Alignment and Local Generality in Federated Learning. - Gihun Lee; Minchan Jeong; Sangmook Kim; Jaehoon Oh; Se-Young Yun (CoRR, 2023)

Hard Prompts Made Interpretable: Sparse Entropy Regularization for Prompt Tuning with RL. - Yunseon Choi; Sangmin Bae; Seonghyun Ban; Minchan Jeong; Chuheng Zhang; Lei Song 001; Li Zhao 007; Jiang Bian 002; Kee-Eung Kim (ACL (1), 2024)

FedSOL: Stabilized Orthogonal Learning with Proximal Restrictions in Federated Learning. - Gihun Lee; Minchan Jeong; Sangmook Kim; Jaehoon Oh; Se-Young Yun (CVPR, 2024)

BAPO: Base-Anchored Preference Optimization for Overcoming Forgetting in Large Language Models Personalization. - Gihun Lee; Minchan Jeong; Yujin Kim; Hojung Jung; Jaehoon Oh; SangMook Kim; Se-Young Yun (EMNLP (Findings), 2024)

Effect of DoS Attack into LiDAR Ethernet. - Yoonji Kim; Insu Oh; Jiung Hwang; Minchan Jeong; Kangbin Yim (IMIS, 2024)

CAN-Based Identification of Human and Autonomous Driving Modes in Level 3 Autonomous Vehicles. - Keunyoung Yu; Donghyun Ryu; Minchan Jeong; Munkhdelgerekh Batzorig; Kangbin Yim (INCoS, 2024)

BAPO: Base-Anchored Preference Optimization for Personalized Alignment in Large Language Models. - Gihun Lee; Minchan Jeong; Yujin Kim; Hojung Jung; Jaehoon Oh; Sangmook Kim; Se-Young Yun (CoRR, 2024)

FedDr+: Stabilizing Dot-regression with Global Feature Distillation for Federated Learning. - Seongyoon Kim; Minchan Jeong; Sungnyun Kim; Sungwoo Cho; Sumyeong Ahn; Se-Young Yun (Trans. Mach. Learn. Res., 2025)

When Debate Fails: Bias Reinforcement in Large Language Models. - Jihwan Oh; Minchan Jeong; Jongwoo Ko; Se-Young Yun (CoRR, 2025)

Efficient Parametric SVD of Koopman Operator for Stochastic Dynamical Systems. - Minchan Jeong; J. Jon Ryu; Se-Young Yun; Gregory W. Wornell (CoRR, 2025)