Whie Jung
whieya [at] kaist.ac.kr
I am a phD student in the school of computing in KAIST, advised by Prof. Seunghoon Hong.
My research focus is on Machine Learning, especially on object-centric learning, disentangled representation learning, and compositional representation learning.
Google Scholar
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Github  / 
CV
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Publications
Disentangled Representation Learning via Modular Compositional Bias
Whie Jung, Dong Hoon Lee, and Seunghoon Hong
Advances in Neural Information Processing Systems (NeurIPS), 2025.
pdf / code
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Bridging the gap to real-world language-grounded visual concept learning
Whie Jung, Semin Kim, Junee Kim, and Seunghoon Hong
Advances in Neural Information Processing Systems (NeurIPS), 2025.
pdf / code
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Learning to Compose: Improving Object Centric Learning by Injecting Compositionality
Whie Jung, Jaehoon Yoo, Sungjin Ahn, and Seunghoon Hong
International Conference on Learning Representations (ICLR), 2024.
pdf / code
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Revisiting hierarchical approach for persistent long-term video prediction
Wonkwang Lee, Whie Jung, Han Zhang, Ting Chen, Jing Yu Koh, Thomas Huang, Hyungsuk Yoon,
Honglak Lee, and Seunghoon Hong
International Conference on Learning Representations (ICLR), 2021.
pdf / code
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Education
2020~ current: Ph.D. student in the School of Computing, KAIST, Daejeon, Korea
2017~2019: M.S. in Graduate School of Culture Technology, KAIST, Daejeon, Korea
2013~2017: B.S. in Enelctrical Engineering, KAIST, Daejeon, Korea
2010~2013: Korea Science Academy, Busan, Korea
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Honors and Awards
NeurIPS 2024 Top Reviewer, 2024
Outstanding TA Award (CS576 Computer Vision), School of Computing, KAIST, 2021
Hyundai Motor Chung Mong-Koo Global Scholarship, 2019
National Science and Technology Scholarship, 2013-2016
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Teaching
2022 KAIST CS576 Computer Vision (Spring)
2021 KAIST Counseling Assistant (Fall)
2021 KAIST CS576 Computer Vision (Spring)
2020 KAIST CS470 Introduction to Artificial Intelligence (Fall)
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Academic Services
Conference Reviewer: ICLR 2024~, CVPR 2024~, ICML 2025, ICCV 2025, NeurIPS 2024~
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Website template from here.
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