publications

2026

1. ICML

   Dual-Stream Diffusion for World-Model Augmented Vision-Language-Action Model

   John Won, Kyungmin Lee, Huiwon Jang, Dongyoung Kim, and Jinwoo Shin

   In International Conference on Machine Learning (ICML), 2026

   arXiv Bib

   @inproceedings{won2026dualstream,
     title = {Dual-Stream Diffusion for World-Model Augmented Vision-Language-Action Model},
     author = {Won, John and Lee, Kyungmin and Jang, Huiwon and Kim, Dongyoung and Shin, Jinwoo},
     booktitle = {International Conference on Machine Learning (ICML)},
     year = {2026},
   }

2. arXiv

   RoboCurate: Harnessing Diversity with Action-Verified Neural Trajectory for Robot Learning

   Seungku Kim, Suhyeok Jang, Byungjun Yoon, Dongyoung Kim, John Won, and Jinwoo Shin

   arXiv preprint arXiv:2602.18742, 2026

   arXiv Bib

   @article{kim2026robocurate,
     title = {RoboCurate: Harnessing Diversity with Action-Verified Neural Trajectory for Robot Learning},
     author = {Kim, Seungku and Jang, Suhyeok and Yoon, Byungjun and Kim, Dongyoung and Won, John and Shin, Jinwoo},
     journal = {arXiv preprint arXiv:2602.18742},
     year = {2026},
   }

3. arXiv

   RLDX-1 Technical Report

   Dongyoung Kim, Huiwon Jang, Myungkyu Koo, Suhyeok Jang, Taeyoung Kim, Beomjun Kim , ..., John Won, and 61 more authors

   2026

   arXiv Bib

   @techreport{kim2026rldx1,
     title = {RLDX-1 Technical Report},
     author = {Kim, Dongyoung and Jang, Huiwon and Koo, Myungkyu and Jang, Suhyeok and Kim, Taeyoung and Kim, Beomjun and Yoon, Byungjun and Jang, Changsung and Choi, Daewon and Han, Dongsu and Lee, Donguk and Kwon, Heeseung and Jeon, Hojin and Kang, Jaehyun and Bae, Jaekyoung and Lee, Jihyuk and Lee, Jimin and Won, John and Ahn, Joonwoo and Park, Junhyeong and Sung, Junyoung and Lee, Kyungmin and Han, Minseong and Yoon, Minsung and Joo, Sejune and Son, Seonil and Park, Seungcheol and Cho, Seunggeun and Moon, Seungjun and Kim, Seungku and Dong, Yonghoon and Cho, Yongjin and Kim, Youngchan and Kim, Chang Hwan and Kim, Dohyeon and Kim, Heecheol and Lee, Heewon and Ahn, Hensen and Ryu, Hyungkyu and Choi, Hyunsoo and Shin, Hyunsoo and Jung, Jaeheon and Kim, Jaewoo and Kim, Jinwook and Chang, Joochul and Kim, Joonsoo and Park, Junghun and Park, Jungwoo and Cho, Junho and Park, Junhyeok and Lee, Junwon and Lee, Kangwook and Kim, Kwanghoon and Choe, Kyoungwhan and Bhadu, Manoj and Oh, Nayoung and Kim, Sangjun and Kim, Sangwoo and Shim, Seunghoon and Kim, Seunghyun and Lee, Seungjun and Ka, Seungyup and Yang, Sungryol and Jung, Wook and Shukla, Yashu and Lee, Yeonjae and Bae, Yeonwoo and Shin, Jinwoo},
     journal = {arXiv preprint arXiv:2605.03269},
     year = {2026},
   }

2025

1. TMLR

   CLIP Meets Diffusion: A Synergistic Approach to Anomaly Detection

   Byeongchan Lee, John Won, Seunghyun Lee, and Jinwoo Shin

   Transactions on Machine Learning Research (TMLR), 2025

   arXiv Bib

   @article{lee2025clipdiffusion,
     title = {CLIP Meets Diffusion: A Synergistic Approach to Anomaly Detection},
     author = {Lee, Byeongchan and Won, John and Lee, Seunghyun and Shin, Jinwoo},
     journal = {Transactions on Machine Learning Research (TMLR)},
     year = {2025},
   }

2023

1. ICLR-W

   Self-Supervised Predictive Coding with Multimodal Fusion for Patient Deterioration Prediction in Fine-Grained Time Resolution

   Kwanhyung Lee, John Won, Heejung Hyun, Sangchul Hahn, Edward Choi, and Joohyung Lee

   In Trustworthy Machine Learning for Healthcare (TML4H), ICLR, 2023

   Best Paper HM Bib

   Best Paper Honorable Mention (3rd Place)

   @inproceedings{lee2023selfsupervised,
     title = {Self-Supervised Predictive Coding with Multimodal Fusion for Patient Deterioration Prediction in Fine-Grained Time Resolution},
     author = {Lee, Kwanhyung and Won, John and Hyun, Heejung and Hahn, Sangchul and Choi, Edward and Lee, Joohyung},
     booktitle = {Trustworthy Machine Learning for Healthcare (TML4H), ICLR},
     year = {2023},
   }

2. ICML-W

   FedSelect: Customized Selection of Parameters for Fine-Tuning during Personalized Federated Learning

   Rishub Tamirisa, John Won, Chengjun Lu, Ron Arel, and Andy Zhou

   In International Workshop on Federated Learning and Analytics in Practice (FL-ICML), 2023

   arXiv Bib

   @inproceedings{tamirisa2023fedselect,
     title = {FedSelect: Customized Selection of Parameters for Fine-Tuning during Personalized Federated Learning},
     author = {Tamirisa, Rishub and Won, John and Lu, Chengjun and Arel, Ron and Zhou, Andy},
     booktitle = {International Workshop on Federated Learning and Analytics in Practice (FL-ICML)},
     year = {2023},
   }