Geon-Hyeong Kim

18 papers A* 11C 1Journal 4Unranked 2
YearRankTypeTitle / Venue / Authors
2026 — conf
IRPO: Implicit Policy Regularized Preference Optimization.
EACL (Findings)
Youngsoo Jang, Yu Jin Kim, Geon-Hyeong Kim, Honglak Lee, Moontae Lee
2025 A* conf
Online Pre-Training for Offline-to-Online Reinforcement Learning.
ICML
Yongjae Shin, Jeonghye Kim, Whiyoung Jung, Sunghoon Hong, Deunsol Yoon, Youngsoo Jang, Geon-Hyeong Kim, Jongseong Chae, Youngchul Sung, Kanghoon Lee, Woohyung Lim
2025 J jnl
SafeDPO: A Simple Approach to Direct Preference Optimization with Enhanced Safety.
CoRR
Geon-Hyeong Kim, Youngsoo Jang, Yu Jin Kim, Byoungjip Kim, Honglak Lee, Kyunghoon Bae, Moontae Lee
2024 A* conf
Degeneration-free Policy Optimization: RL Fine-Tuning for Language Models without Degeneration.
ICML
Youngsoo Jang, Geon-Hyeong Kim, Byoungjip Kim, Yu Jin Kim, Honglak Lee, Moontae Lee
2024 — conf
Prospector: Improving LLM Agents with Self-Asking and Trajectory Ranking.
EMNLP (Findings)
Byoungjip Kim, Youngsoo Jang, Lajanugen Logeswaran, Geon-Hyeong Kim, Yu Jin Kim, Honglak Lee, Moontae Lee
2023 A* conf
Information-Theoretic State Space Model for Multi-View Reinforcement Learning.
ICML
HyeongJoo Hwang, Seokin Seo, Youngsoo Jang, Sungyoon Kim, Geon-Hyeong Kim, Seunghoon Hong, Kee-Eung Kim
2023 A* conf
SafeDICE: Offline Safe Imitation Learning with Non-Preferred Demonstrations.
NeurIPS
Youngsoo Jang, Geon-Hyeong Kim, Jongmin Lee, Sungryull Sohn, Byoungjip Kim, Honglak Lee, Moontae Lee
2022 A* conf
DemoDICE: Offline Imitation Learning with Supplementary Imperfect Demonstrations.
ICLR
Geon-Hyeong Kim, Seokin Seo, Jongmin Lee, Wonseok Jeon, HyeongJoo Hwang, Hongseok Yang, Kee-Eung Kim
2022 J jnl
LobsDICE: Offline Imitation Learning from Observation via Stationary Distribution Correction Estimation.
CoRR
Geon-Hyeong Kim, Jongmin Lee, Youngsoo Jang, Hongseok Yang, Kee-Eung Kim
2022 A* conf
LobsDICE: Offline Learning from Observation via Stationary Distribution Correction Estimation.
NeurIPS
Geon-Hyeong Kim, Jongmin Lee, Youngsoo Jang, Hongseok Yang, Kee-Eung Kim
2021 A* conf
Multi-View Representation Learning via Total Correlation Objective.
NeurIPS
HyeongJoo Hwang, Geon-Hyeong Kim, Seunghoon Hong, Kee-Eung Kim
2020 A* conf
Monte-Carlo Tree Search in Continuous Action Spaces with Value Gradients.
AAAI
Jongmin Lee, Wonseok Jeon, Geon-Hyeong Kim, Kee-Eung Kim
2020 A* conf
Variational Inference for Sequential Data with Future Likelihood Estimates.
ICML
Geon-Hyeong Kim, Youngsoo Jang, Hongseok Yang, Kee-Eung Kim
2020 A* conf
Variational Interaction Information Maximization for Cross-domain Disentanglement.
NeurIPS
HyeongJoo Hwang, Geon-Hyeong Kim, Seunghoon Hong, Kee-Eung Kim
2020 J jnl
Variational Interaction Information Maximization for Cross-domain Disentanglement.
CoRR
HyeongJoo Hwang, Geon-Hyeong Kim, Seunghoon Hong, Kee-Eung Kim
2019 J jnl
Bayesian optimistic Kullback-Leibler exploration.
Mach. Learn.
Kanghoon Lee, Geon-Hyeong Kim, Pedro A. Ortega, Daniel D. Lee, Kee-Eung Kim
2019 C conf
Trust Region Sequential Variational Inference.
ACML
Geon-Hyeong Kim, Youngsoo Jang, Jongmin Lee, Wonseok Jeon, Hongseok Yang, Kee-Eung Kim
2018 A* conf
Monte-Carlo Tree Search for Constrained POMDPs.
NeurIPS
Jongmin Lee, Geon-Hyeong Kim, Pascal Poupart, Kee-Eung Kim