Minchan Jeong

According to our database, Minchan Jeong authored at least 14 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

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

CoRR, 2024

Effect of DoS Attack into LiDAR Ethernet.

Yoonji Kim, Insu Oh, Jiung Hwang, Minchan Jeong, Kangbin Yim

Proceedings of the Innovative Mobile and Internet Services in Ubiquitous Computing, 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

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

FedSOL: Stabilized Orthogonal Learning with Proximal Restrictions in Federated Learning.

Gihun Lee, Minchan Jeong, Sangmook Kim, Jaehoon Oh, Se-Young Yun

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Hard Prompts Made Interpretable: Sparse Entropy Regularization for Prompt Tuning with RL.

Yunseon Choi, Sangmin Bae, Seonghyun Ban, Minchan Jeong, Chuheng Zhang, Lei Song, Li Zhao, Jiang Bian, Kee-Eung Kim

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023

FedSoL: Bridging Global Alignment and Local Generality in Federated Learning.

Gihun Lee, Minchan Jeong, Sangmook Kim, Jaehoon Oh, Se-Young Yun

CoRR, 2023

Bayesian Multi-Task Transfer Learning for Soft Prompt Tuning.

Haeju Lee, Minchan Jeong, Se-Young Yun, Kee-Eung Kim

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 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

Proceedings of the Findings of the Association for Computational Linguistics: EACL 2023, 2023

Toward Risk-based Optimistic Exploration for Cooperative Multi-Agent Reinforcement Learning.

Jihwan Oh, Joonkee Kim, Minchan Jeong, Se-Young Yun

Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

Contextual Linear Bandits under Noisy Features: Towards Bayesian Oracles.

Jung-Hun Kim, Se-Young Yun, Minchan Jeong, Junhyun Nam, Jinwoo Shin, Richard Combes

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Preservation of the Global Knowledge by Not-True Distillation in Federated Learning.

Gihun Lee, Minchan Jeong, Yongjin Shin, Sangmin Bae, Se-Young Yun

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Robust Streaming PCA.

Daniel Bienstock, Minchan Jeong, Apurv Shukla, Se-Young Yun

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

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