| Demodice: Offline imitation learning with supplementary imperfect demonstrations GH Kim, S Seo, J Lee, W Jeon, HJ Hwang, H Yang, KE Kim International Conference on Learning Representations, 2022 | 128 | 2022 |
| Monte-Carlo tree search for constrained POMDPs J Lee, GH Kim, P Poupart, KE Kim Advances in Neural Information Processing Systems 31, 2018 | 95 | 2018 |
| Multi-view representation learning via total correlation objective HJ Hwang, GH Kim, S Hong, KE Kim Advances in Neural Information Processing Systems 34, 12194-12207, 2021 | 65 | 2021 |
| Variational interaction information maximization for cross-domain disentanglement HJ Hwang, GH Kim, S Hong, KE Kim Advances in Neural Information Processing Systems 33, 22479-22491, 2020 | 62 | 2020 |
| Monte-carlo tree search in continuous action spaces with value gradients J Lee, W Jeon, GH Kim, KE Kim Proceedings of the AAAI conference on artificial intelligence 34 (04), 4561-4568, 2020 | 42 | 2020 |
| Lobsdice: Offline learning from observation via stationary distribution correction estimation GH Kim, J Lee, Y Jang, H Yang, KE Kim Advances in Neural Information Processing Systems 35, 8252-8264, 2022 | 35 | 2022 |
| SafeDPO: A simple approach to direct preference optimization with enhanced safety GH Kim, Y Jang, YJ Kim, B Kim, H Lee, K Bae, M Lee arXiv preprint arXiv:2505.20065, 2025 | 15 | 2025 |
| Prospector: Improving LLM agents with self-asking and trajectory ranking B Kim, Y Jang, L Logeswaran, GH Kim, YJ Kim, H Lee, M Lee Findings of the Association for Computational Linguistics: EMNLP 2024, 14958 …, 2024 | 13 | 2024 |
| Variational inference for sequential data with future likelihood estimates GH Kim, Y Jang, H Yang, KE Kim International Conference on Machine Learning, 5296-5305, 2020 | 7 | 2020 |
| Safedice: offline safe imitation learning with non-preferred demonstrations Y Jang, GH Kim, J Lee, S Sohn, B Kim, H Lee, M Lee Advances in Neural Information Processing Systems 36, 74921-74951, 2023 | 6 | 2023 |
| Online pre-training for offline-to-online reinforcement learning Y Shin, J Kim, W Jung, S Hong, D Yoon, Y Jang, G Kim, J Chae, Y Sung, ... arXiv preprint arXiv:2507.08387, 2025 | 5 | 2025 |
| Information-theoretic state space model for multi-view reinforcement learning HJ Hwang, S Seo, Y Jang, S Kim, GH Kim, S Hong, KE Kim | 5 | 2023 |
| Trust region sequential variational inference GH Kim, Y Jang, J Lee, W Jeon, H Yang, KE Kim Asian conference on machine learning, 1033-1048, 2019 | 2 | 2019 |
| Bayesian optimistic kullback–leibler exploration K Lee, GH Kim, P Ortega, DD Lee, KE Kim Machine Learning 108 (5), 765-783, 2019 | 2 | 2019 |
| Degeneration-free policy optimization: RL fine-tuning for language models without degeneration Y Jang, GH Kim, B Kim, YJ Kim, H Lee, M Lee Forty-first International Conference on Machine Learning, 2024 | 1 | 2024 |
| DfPO: Degeneration-free Policy Optimization via Action Masking in Natural Language Action Spaces Y Jang, GH Kim, B Kim, H Lee, M Lee | | |
Kee-Eung KimKAISTVerified email at kaist.ac.kr
