Byeongchan Kim

Byeongchan Kim is a Ph.D. candidate in the Graduate School of Data Science at Seoul National University, under the supervision of Prof. Min-hwan Oh. He received his M.S. in the Graduate School of Data Science under the supervision of Prof. Min-hwan Oh from Seoul National University, and a B.A. in Mathematics and Statistics from Sungkyunkwan University. His research focuses on offline reinforcement learning (RL) algorithms (e.g., model-free, model-based, goal-conditioned, diffusion, etc), kernel methods, optimization, and their various applications.

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Recent News
Sep 2026 2 papers accepted at NeurIPS 2026
Sep 2026 Received the YOULCHON AI Star Scholarship
May 2026 1 paper accepted at ICML 2026
Jan 2026 1 paper accepted at ICLR 2026
Sep 2025 1 paper accepted at NeurIPS 2025
Dec 2023 Received the Hanheum Ok Scholarship
Aug 2023 Received the NRF Ph.D. Fellowship
Apr 2023 1 paper accepted at ICML 2023
Publications
(*Equal contribution)
RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings
Byeongchan Kim*, Arijit Sehanobish*, Avinava Dubey*, Min-hwan Oh, Krzysztof Choromanski*
NeurIPS, 2026
paper / code / project page

Multi-Step Likelihood-Ratio Correction for Reinforcement Learning with Verifiable Rewards
Deokgyu Yoon*, Hyungkyu Kang*, Joongkyu Lee*, Byeongchan Kim, Gyungin Shin, Sungrae Park, Min-hwan Oh
NeurIPS, 2026
paper / code

Latent Representation Alignment for Offline Goal-Conditioned Reinforcement Learning
Hyungkyu Kang*, Byeongchan Kim*, Min-hwan Oh
ICML, 2026
paper / code / project page

Peng's Q(λ) for Conservative Value Estimation in Offline Reinforcement Learning
Byeongchan Kim, Min-hwan Oh
ICLR, 2026
paper / code

EUGens: Efficient, Unified and General Dense Layers
Sang Min Kim*, Byeongchan Kim*, Arijit Sehanobish*, Somnath Basu Roy Chowdhury*, Rahul Kidambi*, Dongseok Shim, Avinava Dubey*, Snigdha Chaturvedi, Min-hwan Oh, Krzysztof Choromanski*
NeurIPS, 2025
paper / code

Model-based Offline Reinforcement Learning with Count-based Conservatism
Byeongchan Kim, Min-hwan Oh
ICML, 2023
(M.S. Thesis)
paper / code


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