Ju-Seung Byun
Ju-Seung Byun
Ph.D. Student
The Ohio State University
Computer Science & Engineering

About me

My name is Ju-Seung Byun. I am a forth-year computer science & engineering Ph.D. student at The Ohio State University advised by Andrew Perrault. My research interests are in deep reinforcement learning, especially focusing on hierarchical structure and distributional reinforcement learning.

Before I came to OSU, I received my Master’s degree from University of Southern California (2019) and Bachelor’s degree from Inha University (2017) in South Korea, both in Computer Science.


(Preprint) ARES: Alternating Reinforcement Learning and Supervised Fine-Tuning for Enhanced Multi-Modal Chain-of-Thought Reasoning Through Diverse AI Feedback
Ju-Seung Byun*, Jiyun Chun*, Jihyng Kil, Andrew Perrault
arxiv 2024 / Paper / Code
(Preprint) Symmetric Reinforcement Learning Loss for Robust Learning on Diverse Tasks and Model Scales
Ju-Seung Byun, Andrew Perrault
arxiv 2024 / Paper / Code
(Preprint) Reinforcement Learning for Fine-tuning Text-to-speech Diffusion Models
Jingyi Chen, Ju-Seung Byun, Micha Elsner, Andrew Perrault
arxiv 2024 / Paper
SalsaBot: Towards a Robust and Generalizable Embodied Agent
Chan Hee Song*, Jiaman Wu* Ju-Seung Byun, Zexin Xu, Vardaan Pahuja, Goonmeet Bajaj, Samuel Stevens, Ziru Chen, Yu Su
Embodied AI Workshop at CVPR 2023 / Paper (Short)
Alexa Prize SimBot Challenge Proceedings 2023 / Paper (Long)
(Preprint) Normality-Guided Distributional Reinforcement Learning for Continuous Control
Ju-Seung Byun, Andrew Perrault
arXiv 2023 / Paper / Code
Training Transition Policies via Distribution Matching for Complex Tasks
Ju-Seung Byun, Andrew Perrault
ICLR 2022 / Paper / Code / Video
Proximal Policy Gradient: PPO with Policy Gradient
Ju-Seung Byun, Byungmoon Kim, Huamin Wang
arXiv 2020 / Paper / Code