Dongwon Kim

Dongwon Kim

Postdoctoral Researcher, KAIST
kdwon@postech.ac.kr
world model / representation learning / multi-modal learning

I am a postdoctoral researcher at KAIST, working with Prof. Jeany Son. I previously completed my BS and PhD at POSTECH CVLab where I worked with Prof. Suha Kwak. My research centers on whether machines can learn representations with the right abstraction and hierarchy, spanning work in compositional representation (SelfMod), multi-modalities (DivE, SaG, MaskGen), and world model (ongoing, CompACT).

News 01 / 13

24 Sep 2026 A paper on generation-friendly image tokenization is accepted at NeurIPS 2026 (arXiv).

all news

Publications

Highlighted: first, co-first, or co-corresponding author · * equal contribution · † co-corresponding

  1. arXiv 2026 V+L
    EventCoT: Event-centric Video Chain-of-thought for Reasoning Temporal Localization
    Youngkil Song, Yoonjae Baek, Dongwon Kim, Inho Kim, Dongkeun Kim, and Suha Kwak
    arXiv 2026
    [arXiv]
  2. arXiv 2026 WM
    ACID: Action Consistency via Inverse Dynamics for Planning with World Models
    Gawon Seo, Dongwon Kim†, and Suha Kwak†
    arXiv 2026
    [arXiv]
  3. CVPR 2026 WM·GEN
    Planning in 8 Tokens: A Compact Discrete Tokenizer for Latent World Model
    Dongwon Kim, Gawon Seo, Jinsung Lee, Minsu Cho, and Suha Kwak
    CVPR 2026
    (An early version appeared in LSRW workshop in CoRL 2025)
    [arXiv][Code][Website]
  4. NeurIPS 2026 GEN
    Structured State-Space Regularization for Generation-Friendly Image Tokenization
    Jinsung Lee, Jaemin Oh, Namhun Kim, Dongwon Kim, Byung-Jun Yoon, and Suha Kwak
    NeurIPS 2026
    [arXiv]
  5. ICCV 2025 GEN·V+L
    Democratizing Text-to-Image Masked Generative Models with Compact Text-Aware One-Dimensional Tokens
    Dongwon Kim*, Ju He*, Qihang Yu*, Chenglin Yang, Xiaohui Shen, Suha Kwak, and Liang-Chieh Chen
    ICCV 2025
    [arXiv][PDF][Code]
    Democratizing Text-to-Image Masked Generative Models with Compact Text-Aware One-Dimensional Tokens preview
  6. arXiv 2024 GEN
    1.58-bit FLUX
    Chenglin Yang, Celong Liu, Xueqing Deng, Dongwon Kim, Xing Mei, Xiaohui Shen, and Liang-Chieh Chen
    arXiv 2024
    [arXiv]
    1.58-bit FLUX preview
  7. NeurIPS 2024 REP
    Bootstrapping Top-down Information for Self-modulating Slot Attention
    Dongwon Kim, Seoyeon Kim, and Suha Kwak
    NeurIPS 2024
    [arXiv][Code]
  8. ECCV 2024 V+L
    PLOT: Text-based Person Search with Part Slot Attention for Corresponding Part Discovery
    Jicheol Park, Dongwon Kim, Boseung Jeong, and Suha Kwak
    ECCV 2024
    PLOT: Text-based Person Search with Part Slot Attention for Corresponding Part Discovery preview
  9. NAACL 2024 V+L
    Extending CLIP’s Image-Text Alignment to Referring Image Segmentation
    Seoyeon Kim, Minguk Kang, Dongwon Kim, Jaesik Park, and Suha Kwak
    NAACL 2024
    [Code]
    Extending CLIP’s Image-Text Alignment to Referring Image Segmentation preview
  10. ICCV 2023 V+L
    Shatter and Gather: Learning Referring Image Segmentation with Text Supervision
    Dongwon Kim*, Namyup Kim*, Cuiling Lan, and Suha Kwak
    ICCV 2023
    [arXiv][Code][Website]
    Shatter and Gather: Learning Referring Image Segmentation with Text Supervision preview
  11. CVPR 2023 V+L
    Improving Cross-Modal Retrieval With Set of Diverse Embeddings
    Dongwon Kim, Namyup Kim, and Suha Kwak
    CVPR 2023Highlight, 235/9155 = 2.5%
    [arXiv][Code][Website]
    Improving Cross-Modal Retrieval With Set of Diverse Embeddings preview
  12. CVPR 2022 V+L
    ReSTR: Convolution-Free Referring Image Segmentation Using Transformers
    Namyup Kim, Dongwon Kim, Cuiling Lan, Wenjun Zeng, and Suha Kwak
    CVPR 2022
    [arXiv][Website]
    ReSTR: Convolution-Free Referring Image Segmentation Using Transformers preview
  13. CVPR 2022 REP
    Self-Taught Metric Learning Without Labels
    Sungyeon Kim, Dongwon Kim, Minsu Cho, and Suha Kwak
    CVPR 2022
    [arXiv][Code][Website]
    Self-Taught Metric Learning Without Labels preview
  14. CVPR 2021 REP
    Embedding Transfer With Label Relaxation for Improved Metric Learning
    Sungyeon Kim, Dongwon Kim, Minsu Cho, and Suha Kwak
    CVPR 2021
    [arXiv][Website]
    Embedding Transfer With Label Relaxation for Improved Metric Learning preview
  15. CVPR 2020 REP
    Proxy Anchor Loss for Deep Metric Learning
    Sungyeon Kim, Dongwon Kim, Minsu Cho, and Suha Kwak
    CVPR 2020
    [arXiv][Code][Website]
    Proxy Anchor Loss for Deep Metric Learning preview

Experience

2025 – Now Postdoctoral researcher · KAIST, Daejeon, KR
InnoCORE-LLM, PI: Jeany Son
2024 Research Intern · Fundamental Research Team, ByteDance SEED, San Jose, US
Developed efficient text-to-image generative model using 1D tokens (MaskGen)

Education

2019 – 2025 Integrated M.S & Ph.D in Computer Science & Engineering
POSTECH, Pohang, South Korea
Advisor: Prof. Suha Kwak
2015 – 2019 B.S. in Computer Science & Engineering
POSTECH, Pohang, South Korea

Honors and Awards

POSTECH CSE Best Research Award, POSTECH, 2025

POSTECHIAN Fellowship, POSTECH, 2023

  • $5,000 grant

BK21 Best Paper Award, POSTECH GSAI, 2023

  • Self-Taught Metric Learning without Labels (CVPR 2022)

Qualcomm Innovation Fellowship Winner, Qualcomm Korea Corp., 2022

  • Self-Taught Metric Learning without Labels (CVPR 2022)
  • ReSTR: Convolution-free Referring Image Segmentation Using Transformers (CVPR 2022)

NAVER x POSTECH AI DAY The 2nd and 3rd Prize, 2022

  • ReSTR: Convolution-free Referring Image Segmentation Using Transformers (CVPR 2022)

Qualcomm Innovation Fellowship Winner, Qualcomm Korea Corp., 2021

  • Embedding Transfer with Label Relaxation for Improved Metric Learning (CVPR 2021)

IPIU Best Paper Award, 2021

  • Embedding Transfer with Label Relaxation for Improved Metric Learning (CVPR 2021)

Professional Services

Reviewer
  • IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
  • IEEE/CVF International Conference on Computer Vision (ICCV)
  • IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • European Conference on Computer Vision (ECCV)
  • Winter Conference on Applications of Computer Vision (WACV)
  • Asian Conference on Computer Vision (ACCV)
  • Conference on Neural Information Processing Systems (NeurIPS)