Seongheon Park

Contact. seongheon_park [at] cs [dot] wisc [dot] edu  |  CV

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1210 W Dayton St

Madison, WI 53706

Hello! I’m a third-year Ph.D. student in the Department of Computer Sciences at the University of Wisconsin-Madison, where I am fortunate to be advised by Prof. Sharon Li. Previously, I received my M.S. and B.S. degrees in Electrical and Electronic Engineering from Yonsei University, where I was advised by Prof. Kwanghoon Sohn and Prof. Kibok Lee.

My research focuses on making foundation models (LLMs, LVLMs, and VLAs) safe and reliable in real-world deployment. Specifically, I study why and how these models fail and how to monitor and correct them through:

  • Failure detection, mitigation, and recovery
  • Failure reasoning and diagnosis
  • Latent-space interpretability

These are crucial for preventing catastrophic failures in human-facing and industrial applications, and for enabling robust agentic systems to stop, replan, and incorporate human intervention in an interpretable way. I am also broadly interested in multimodal models and post-training.

News

Sep 24, 2026 Two papers have been accepted to NeurIPS 2026! 🌟
Sep 21, 2026 Excited to start my Student Researcher position at Google Google G
May 18, 2026 I will be joining Microsoft Research Asia-Tokyo this May as a research intern, working on Embodied AI agents Microsoft
Apr 14, 2026 I have passed my PhD qualifying exam! :tada:
Apr 06, 2026 Two papers have been accepted to ACL 2026!

Professional Experience

  • Google

    Sep 2026 – Present

    Student Researcher · LLM agents

    New York, United States

  • Microsoft Research Asia–Tokyo

    May 2026 – Aug 2026

    Research Intern · VLAs

    Tokyo, Japan

Selected Publications

All publications are listed on Google Scholar.

  1. NeurIPS
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    Hide-and-Seek in Trajectories: Discovering Failure Signals for VLA Runtime Monitoring
    Seongheon Park, Wendi Li, Changdae Oh, Samuel Yeh, Zsolt Kira, Michael Hagenow, and Sharon Li
    Conference on Neural Information Processing Systems, Sep 2026
  2. NeurIPS
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    Neglected Free Lunch from Post-training: Progress Advantage for LLM Agents
    Changdae Oh, Wendi Li, Seongheon Park, Samuel Yeh, Tanwi Mallick, and Sharon Li
    Conference on Neural Information Processing Systems, Sep 2026
  3. ACL (Main)
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    Uncertainty Quantification in LLM Agents: Foundations, Emerging Challenges, and Opportunities
    Changdae Oh, Seongheon Park, Toeun Kim, Jiatong Li, Wendi Li, Samuel Yeh, Xuefeng Du, Hamed Hassani, Paul Bogdan, Dawn Song, and Sharon Li
    Annual Meeting of the Association for Computational Linguistics, Feb 2026
  4. ACL (Findings)
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    VAUQ: Vision-Aware Uncertainty Quantification for LVLM Self-Evaluation
    Seongheon Park, Changdae Oh, Hyeongkyu Choi, Xuefeng Du, and Sharon Li
    Annual Meeting of the Association for Computational Linguistics, Jan 2026
  5. NeurIPS
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    GLSim: Detecting Object Hallucinations in LVLMs via Global-Local Similarity
    Seongheon Park, and Yixuan Li
    Conference on Neural Information Processing Systems, Jul 2025
  6. ICML
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    Steer LLM Latents for Hallucination Detection
    Seongheon Park, Xuefeng Du, Min-Hsuan Yeh, and Yixuan Li
    International Conference on Machine Learning, May 2025
  7. CVPR Workshop
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    Rethinking Open-World Semi-Supervised Learning: Distribution Mismatch and Inductive Inference
    Seongheon Park*, Hyuk Kwon*, Kwanghoon Sohn, and Kibok Lee
    CVPR Workshop on Computer Vision in the Wild, Jun 2024
  8. WACV
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    Normality guided multiple instance learning for weakly supervised video anomaly detection
    Seongheon Park, Hanjae Kim, Minsu Kim, Dahye Kim, and Kwanghoon Sohn
    IEEE/CVF Winter Conference on Applications of Computer Vision, Jan 2023

Reviewer Experience

  • Conference: CVPR, ECCV, ACL, NeurIPS, ICLR, AAAI
  • Journal: TPAMI, PR

Miscellaneous

Outside of research, I love playing the piano 🎹, listening to all kinds of music and attending concerts 🎶, and exploring art and architecture 🎨🏛️. If you share any of these interests, I’d love to connect!

Languages 🌐

Korean (Native), English, Japanese (JLPT N1)