6 papers
HorizonFlow: Variable-Length Planning for Offline Goal-Conditioned RL
JunHyeok Oh, Zian Jang, Byung-Jun Lee
Recent advances in generative planning have made trajectory inpainting a promising approach to offline goal-conditioned reinforcement learning. However, these methods typically spe…
TABX: A High-Throughput Sandbox Battle Simulator for Multi-Agent Reinforcement Learning
Hayeong Lee, JunHyeok Oh, Byung-Jun Lee
The design of environments plays a critical role in shaping the development and evaluation of cooperative multi-agent reinforcement learning (MARL) algorithms. While existing bench…
Iterative Prompt Refinement for Safer Text-to-Image Generation
Jinwoo Jeon, JunHyeok Oh, Hayeong Lee +1
Text-to-Image (T2I) models have made remarkable progress in generating images from text prompts, but their output quality and safety still depend heavily on how prompts are phrased…
Offline Reinforcement Learning with Penalized Action Noise Injection
JunHyeok Oh, Byung-Jun Lee
Offline reinforcement learning (RL) optimizes a policy using only a fixed dataset, making it a practical approach in scenarios where interaction with the environment is costly. Due…
Rethinking DPO: The Role of Rejected Responses in Preference Misalignment
Jay Hyeon Cho, JunHyeok Oh, Myunsoo Kim +1
Direct Preference Optimization (DPO) is a simple and efficient framework that has attracted substantial attention. However, it often struggles to meet its primary objectives -- inc…
Prior-Guided Diffusion Planning for Offline Reinforcement Learning
Donghyeon Ki, JunHyeok Oh, Seong-Woong Shim +1
Diffusion models have recently gained prominence in offline reinforcement learning due to their ability to effectively learn high-performing, generalizable policies from static dat…