| 2024 | ACL | 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 |
| 2024 | CVPR | FedSOL: Stabilized Orthogonal Learning with Proximal Restrictions in Federated Learning. | Gihun Lee, Minchan Jeong, Sangmook Kim, Jaehoon Oh, Se-Young Yun |
| 2024 | EMNLP | 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 |
| 2023 | AISTATS | Contextual Linear Bandits under Noisy Features: Towards Bayesian Oracles. | Jung-Hun Kim, Se-Young Yun, Minchan Jeong, Junhyun Nam, Jinwoo Shin, Richard Combes |
| 2023 | EACL | 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 |
| 2023 | EMNLP | Bayesian Multi-Task Transfer Learning for Soft Prompt Tuning. | Haeju Lee, Minchan Jeong, Se-Young Yun, Kee-Eung Kim |