Minseong Bae

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I am a M.S. student at KAIST MLV Lab (School of Computing), advised by Prof. Hyunwoo J. Kim. Previously, I received my B.E. in Computer Science and Engineering and Mathematics from Korea University in 2025. For more details, please see my CV.

My research interests lie in generative modeling across diverse modalities and geometric deep learning, particularly in their applications to the natural sciences for tackling impactful real-world problems (AI4Science).

Recently, I have been particularly interested in generative model-based world modeling, reward-guided generation, and agentic systems for scientific modeling and discovery. Through these directions, I aim to develop methods that integrate reasoning, generative modeling, and representation learning to model, simulate, and optimize complex scientific phenomena.

My long-term research goal is to build robust and scalable learning frameworks that support the scientific research loop and enable self-improving, human-collaborative agents for scientific discovery.

Feel free to reach out via email if you’d like to discuss anything related to me!

news

Mar 25, 2026 Our new preprint 🌹F⁴Splat is now available on arXiv! You can also check our project page!
Nov 08, 2025 Our 2 papers (TabFlash and CoLLaMo) are accepted to AAAI 2026! 🇸🇬
Sep 01, 2025 I graduated from Korea University and officially started my M.S. course in KAIST!

latest posts

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selected publications

  1. arXiv
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    F⁴Splat: Feed-Forward Predictive Densification for Feed-Forward 3D Gaussian Splatting
    Injae Kim, Chaehyeon Kim, Minseong Bae, Minseok Joo, and Hyunwoo J Kim
    In arXiv preprint, 2026
  2. AAAI
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    TabFlash: Efficient Table Understanding with Progressive Question Conditioning and Token Focusing
    Jongha Kim, Minseong Bae, Sanghyeok Lee, Jinsung Yoon, and Hyunwoo J Kim
    In The 40th AAAI Conference on Artificial Intelligence (AAAI), 2026
  3. AAAI
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    Improving Large Molecular Language Model via Relation-aware Multimodal Collaboration
    Jinyoung Park, Minseong Bae, Jeehye Na, and Hyunwoo J Kim
    In The 40th AAAI Conference on Artificial Intelligence (AAAI), 2026
  4. NeurIPS
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    LLaMo: Large Language Model-based Molecular Graph Assistant
    Jinyoung Park, Minseong Bae, Dohwan Ko, and Hyunwoo J Kim
    In The 38th Conference on Neural Information Processing Systems (NeurIPS), 2024