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Jongwon Jeong

Jongwon Jeong

 CV / GoogleScholar / Github / LinkedIn

Ph.D. Student at University of Wisconsin-Madison

Contact

  • Email: jsjsjs964@gmail.com (Permanent), jongwon.jeong@wisc.edu

Biography

Hello. I am a first-year Ph.D. student in Electrical and Computer Engineering (ECE) at the University of Wisconsin-Madison, supervised by Prof. Kangwook Lee. 

Previously, I was a deep learning research engineer at Deep Learning Div. in KRAFTON. Also, I was an AI researcher at Applied AI Lab, NLP Center in NCSOFT Corp.
I received B.S. and M.S. degrees in Electrical Engineering (EE) from Korea Advanced Institute of Science and Technology (KAIST) in 2018 and 2020, respectively, supervised by Prof. Sae-Young Chung.

Research Interest

My research interests lie in Language Model (LM) Agents that can plan, reason, and use external tools to interact with real-world environments and accomplish complex tasks. My work particularly focuses on identifying the limitations of their agentic capabilities and on developing empirical and theoretical methods to overcome these limitations. I have also worked on data-centric artificial intelligence (AI) to build practical and efficient LM agents, such as small language models (sLMs), for deployment on edge devices. From an application perspective, my interests also extend to applying LM agents to diverse domains such as graph learning, recommender systems, game AI, and embodied AI.

Research Keywords

  • Language Model Agents, Tool-augmented Reasoning, Data-centric AI, Small Language Models (sLMs).

  • Graph Learning, Recommender Systems (RS), Game AI, Embodied AI

News

  • (Sep. 2025) 🎉 Our paper “Distilling LLM Agents into Small Models with Retrieval and Code Tools” has been accepted at NeurIPS 2025 (Spotlight)!
                                    Huge thanks to my collaborators, especially Minki, for the incredible collaboration 🙌.

  • (Aug. 2025) 🎓✨ Excited to start my new academic journey at UW–Madison!

Papers

P: Preprint, C: Conference

  • [P3] Distilling LLM Agent into Small Models with Retrieval and Code Tools
    Minki Kang, Jongwon Jeong, Seanie Lee, Jaewoong Cho, Sung Ju Hwang
    Neural Information Processing Systems (NeurIPS) 2025. (Spotlight, Accepted)

  • [P2] T1: Tool-integrated Self-verification for Test-time Compute Scaling in Small Language Models
    Minki Kang*, Jongwon Jeong*, Jaewoong Cho (*: Equally Contributed)
    arXiv, 2025. (Preprint)

  • [C3] How to Move Your Dragon: Text-to-Motion Synthesis for Large-Vocabulary Objects
    Wonkwang Lee, Jongwon Jeong*, Taehong Moon*, Hyeon-Jong Kim, Jaehyeon Kim, Gunhee Kim, Byeong-Uk Lee  (*: Equally Contributed)
    International Conference on Machine Learning (ICML) 2025.

  • [C2] iGraphMix: Input Graph Mixup Method for Node Classification
    Jongwon Jeong, Hoyeop Lee, Hyui Geon Yoon, Beomyoung Lee, Junhee Heo, Geonsoo Kim, Kim Jin Seon
    International Conference on Learning Representations (ICLR) 2024.

  • [P1] Human-like Evaluation Paradigms for Post-hoc Explanation Method Using Masked Language Model
    Vinnam Kim*, Jongwon Jeong*, Hyunsouk Cho, and Jeong Choi (*: Equally Contributed)
    Preprint, 2023.

  • [C1] FPAdaMetric: False-Positive-Aware Adaptive Metric Learning for Session-Based Recommendation
    Jongwon Jeong, Jeong Choi, Hyunsouk Cho, and Sehee Chung
    Proceedings of the AAAI Conference on Artificial Intelligence (AAAI) 2022, 36(4), 4039-4047.

Educations

  • Ph.D. in Electrical and Computer Engineering, University of Wisconsin-Madison, Sep 2025 – Present

  • M.S. in Electrical Engineering, KAIST, Aug. 2018 – Aug. 2020.

  • B.S. in Electrical Engineering (Cum Laude), KAIST, Mar. 2014 – Aug. 2018.

  • Korea Science Academy of KAIST, Mar. 2011 – Feb. 2014.

Work Experience

  • KRAFTON Inc., Oct.2023 – Aug. 2025.
    Deep Learning Research Engineer at Natural Language DL Team., Applied DL Dept., Deep Learning Div. (Full-time)

  • NCSOFT Corp., Aug. 2020 – Oct. 2023.
    AI Researcher at Applied AI Lab., NLP Center. (Full-time)
    Fulfilled alternative mandatory military service for Sep. 2020 – Sep. 2023.

  • Koh Young Technology, Mar. 2017 – Aug. 2017.
    Research Intern at Medical Vision Team. (Internship)
    KAIST EE Co-op Program

Honors

  • Top Reviewer, Learning on Graphs (LoG), Nov. 2024.

  • Graduation with Honors (Cum Laude), KAIST, Aug. 2018.

  • National Science & Engineering Scholarship, Mar. 2016 – Mar. 2018.

Contact: jongwon.jeong@wisc.edu
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