Park, Seohong

24 publications

ICLR 2026 Decoupled Q-Chunking Qiyang Li, Seohong Park, Sergey Levine

ICLR 2026 Dual Goal Representations Seohong Park, Deepinder Mann, Sergey Levine

ICLR 2026 Intention-Conditioned Flow Occupancy Models Chongyi Zheng, Seohong Park, Sergey Levine, Benjamin Eysenbach

ICLR 2026 Scalable Offline Model-Based RL with Action Chunks Kwanyoung Park, Seohong Park, Youngwoon Lee, Sergey Levine

ICLR 2026 Transitive RL: Value Learning via Divide and Conquer Seohong Park, Aditya Oberai, Pranav Atreya, Sergey Levine

ICML 2025 Flow Q-Learning Seohong Park, Qiyang Li, Sergey Levine

NeurIPS 2025 Horizon Reduction Makes RL Scalable Seohong Park, Kevin Frans, Deepinder Mann, Benjamin Eysenbach, Aviral Kumar, Sergey Levine

ICLR 2025 OGBench: Benchmarking Offline Goal-Conditioned RL Seohong Park, Kevin Frans, Benjamin Eysenbach, Sergey Levine

CoRL 2025 Steering Your Diffusion Policy with Latent Space Reinforcement Learning Andrew Wagenmaker, Yunchu Zhang, Mitsuhiko Nakamoto, Seohong Park, Waleed Yagoub, Anusha Nagabandi, Abhishek Gupta, Sergey Levine

ICML 2024 Foundation Policies with Hilbert Representations Seohong Park, Tobias Kreiman, Sergey Levine

NeurIPS 2024 Is Value Learning Really the Main Bottleneck in Offline RL? Seohong Park, Kevin Frans, Sergey Levine, Aviral Kumar

ICMLW 2024 Is Value Learning Really the Main Bottleneck in Offline RL? Seohong Park, Kevin Frans, Sergey Levine, Aviral Kumar

ICLR 2024 METRA: Scalable Unsupervised RL with Metric-Aware Abstraction Seohong Park, Oleh Rybkin, Sergey Levine

ICML 2024 Unsupervised Zero-Shot Reinforcement Learning via Functional Reward Encodings Kevin Frans, Seohong Park, Pieter Abbeel, Sergey Levine

ICML 2023 Controllability-Aware Unsupervised Skill Discovery Seohong Park, Kimin Lee, Youngwoon Lee, Pieter Abbeel

NeurIPS 2023 HIQL: Offline Goal-Conditioned RL with Latent States as Actions Seohong Park, Dibya Ghosh, Benjamin Eysenbach, Sergey Levine

NeurIPSW 2023 METRA: Scalable Unsupervised RL with Metric-Aware Abstraction Seohong Park, Oleh Rybkin, Sergey Levine

NeurIPSW 2023 METRA: Scalable Unsupervised RL with Metric-Aware Abstraction Seohong Park, Oleh Rybkin, Sergey Levine

ICMLW 2023 Offline Goal-Conditioned RL with Latent States as Actions Seohong Park, Dibya Ghosh, Benjamin Eysenbach, Sergey Levine

ICML 2023 Predictable MDP Abstraction for Unsupervised Model-Based RL Seohong Park, Sergey Levine

NeurIPS 2022 Constrained GPI for Zero-Shot Transfer in Reinforcement Learning Jaekyeom Kim, Seohong Park, Gunhee Kim

ICLR 2022 Lipschitz-Constrained Unsupervised Skill Discovery Seohong Park, Jongwook Choi, Jaekyeom Kim, Honglak Lee, Gunhee Kim

NeurIPS 2021 Time Discretization-Invariant Safe Action Repetition for Policy Gradient Methods Seohong Park, Jaekyeom Kim, Gunhee Kim

ICML 2021 Unsupervised Skill Discovery with Bottleneck Option Learning Jaekyeom Kim, Seohong Park, Gunhee Kim