Dongyoon Hwang

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Hi! I am a Ph.D. candidate at KAIST AI (DAVIAN Lab), advised by Jaegul Choo.

I am interested in building general-purpose robots that can reliably perceive, reason, and act in the unstructured physical world. My research centers on two directions: (i) grounding robot foundation models in explicit 3D geometry to connect perception with action, and (ii) developing scalable and data-efficient reinforcement learning methods that enable robots to acquire robust control policies through interaction with their environments.

Previously, I was a research intern at Krafton AI and Naver Labs Europe, and received my B.S. in Computer Science from Korea University.

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Publications

    Selected  /  All

preprint2026pointmapvla

PointmapVLA: Scaling Robot Learning with Robot-Centric Pointmaps
Dongyoon Hwang*, Dongjin Kim*, Byungkun Lee*, Kyungmin Lee, Dohyun Lee, Hojoon Lee, Minho Park, Jaegul Choo. (* Equal contribution)
Preprint'26.
project page / paper / code
preprint2026flashdex

FlashDexRetarget: Accelerating Dexterous Manipulation Data Generation through Multi-Motion Retargeting
Kyungmin Lee*, Sibeen Kim*, Dongyoon Hwang*, Yoonsang Oh*, Donghu Kim, Youngdo Lee, I Made Aswin Nahrendra, Jaegul Choo, Hojoon Lee. (* Equal contribution)
Preprint'26.
project page / arXiv / code
preprint2026pointmap

See like a Robot: Robot-Centric Pointmaps for VLA Models
Byungkun Lee*, Dongyoon Hwang*, Dongjin Kim, Hojoon Lee, Hyunseung Kim, Jaegul Choo, Minho Park. (* Equal contribution)
Preprint'26.
project page / arXiv
corl2026pam

An Agentic Framework for Proactive Robots with Procedural Assistance Memory
Dohyun Lee*, Minho Park*, Jeonghoon Park, Dongyoon Hwang, Junha Hyung, Sungwon Hwang, Byungkun Lee, Jaegul Choo. (* Equal contribution)
CoRL'26.
project page / arXiv / code
corl2026phuma

PHUMA: Physically Reliable Humanoid Locomotion Dataset
Kyungmin Lee*, Sibeen Kim*, Youngdo Lee, Minho Park, Hyunseung Kim, Dongyoon Hwang, Donghu Kim, Hojoon Lee, Jaegul Choo. (* Equal contribution)
CoRL'26, Spotlight.
project page / arXiv / code / dataset
iros2026hamster

3D HAMSTER: Bridging Planning and Control in Hierarchical Vision Language Action Models through 3D Trajectory Guidance
Dongyoon Hwang*, Byungkun Lee*, Dongjin Kim*, Hyojin Jang, Hoiyeong Jin, Jueun Mun, Minho Park, Hojoon Lee, Hyunseung Kim, Jaegul Choo. (* Equal contribution)
IROS'26.
project page / arXiv / code / HF models
colm2025chess

Can Large Language Models Develop Strategic Reasoning? Post-training Insights from Learning Chess
Dongyoon Hwang*, Hojoon Lee*, Jaegul Choo, Dongmin Park, Jongho Park. (* Equal contribution)
CoLM'25, SCALR Workshop.
arXiv
iclr2025simba

SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning
Hojoon Lee*, Dongyoon Hwang*, Donghu Kim, Hyunseung Kim, Jun Jet Tai, Kaushik Subramanian, Peter R. Wurman, Jaegul Choo, Peter Stone, Takuma Seno. (* Equal contribution)
ICLR'25, Spotlight (top 5%).
project page / arXiv / code
neurips2024dodont

Do’s and Don’ts: Learning Desirable Skills with Instruction Videos
Hyunseung Kim, Byungkun Lee, Hojoon Lee, Dongyoon Hwang, Donghu Kim, Jaegul Choo.
NeurIPS'24.
project page / arXiv
icml2024coin

CoIn: Adapting Pretrained ViTs with Convolution Injector for Visuo-Motor Control
Dongyoon Hwang*, Byungkun Lee*, Hojoon Lee, Hyunseung Kim, Jaegul Choo. (* Equal contribution)
ICML'24.
project page / arXiv / code
icml2024atari-pb

ATARI-PB: Investigating Pre-Training Objectives for Generalization in Vision-Based Reinforcement Learning
Donghu Kim*, Hojoon Lee*, Kyungmin Lee*, Dongyoon Hwang, Jaegul Choo. (* Equal contribution)
ICML'24.
project page / arXiv
tors2024sardine

SARDINE: Simulator for Automated Recommendation in Dynamic and Interactive Environments
Romain Deffayet, Thibaut Thonet, Dongyoon Hwang, Vassilissa Lehoux, Jean-Michel Renders, Maarten de Rijke.
ACM TORS'24.
paper / code
neurips2023disco-dance

DISCO-DANCE: Learning to Discover Skills through Guidance
Hyunseung Kim*, Byungkun Lee*, Hojoon Lee, Dongyoon Hwang, Sejik Park, Kyushik Min, Jaegul Choo. (* Equal contribution)
NeurIPS'23.
project page / arXiv / code / Bibtex
icml2023simtpr

SimTPR: On the Importance of Feature Decorrelation for Unsupervised Representation Learning in Reinforcement Learning
Hojoon Lee, Koanho Lee, Dongyoon Hwang, Hyunho Lee, Byungkun Lee, Jaegul Choo.
ICML'23.
arXiv / code / poster / Bibtex
sigir2022irs

Towards Validating Long-Term User Feedbacks in Interactive Recommendation Systems
Hojoon Lee, Dongyoon Hwang, Kyushik Min, Jaegul Choo.
SIGIR'22 (short), Best Short Paper Honorable Mention.
paper / poster / Bibtex
www2022draftrec

DraftRec: Personalized Draft Recommendation for Winning in Multi-Player Online Battle Arena Games
Hojoon Lee*, Dongyoon Hwang*, Hyunseung Kim, Byungkun Lee, Jaegul Choo. (* Equal contribution)
WWW'22.
arXiv / code / poster / Bibtex
preprint2021moimixer

MOI-Mixer: Improving MLP-Mixer with Multi Order Interactions in Sequential Recommendation
Hojoon Lee, Dongyoon Hwang, Sunghwan Hong, Changyeon Kim, Seungryong Kim, Jaegul Choo.
Preprint'21.
arXiv

Work Experience

Krafton AI Nov 2024 - Nov 2025
Research Intern Seoul, Korea
  • Built an AI co-playable character (CPC) for PUBG Ally on top of LLM/VLM-based agent systems. demo
  • PUBG Ally debuted at CES 2025 as a joint showcase with NVIDIA and later entered beta in PUBG: BATTLEGROUNDS. news
  • Developed an LLM-based chess-reasoning agent post-trained with reinforcement learning. paper
Naver Labs Europe Nov 2022 - Feb 2023
Research Intern Grenoble, France
  • Studied representation learning for RL-based recommender systems. paper

Other activities

Awards
  • Spotlight Presentation (top 5%), SimBa, ICLR, 2025.
  • Best Short Paper Honorable Mention Award, ACM SIGIR, 2022.
  • Graduation Project Award, Silver Prize ($2,000 as awards), Korea University, 2021.

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