About Me

Hello! I am an incoming Ph.D. student in Computer Science and Engineering at the University of Michigan, where I will be advised by Prof. Lu Wang. Currently, I am a research intern at the Vision & Learning Lab at Seoul National University, advised by Prof. Gunhee Kim.

My primary research interests lie in natural language processing and machine learning, with a focus on building sustainable, general-purpose AI systems that can adapt to dynamic and evolving environments.

Publications

  • GradNormIR: When Should We Update the Dense Retriever in Evolving Corpora?

    Dayoon Ko, Jinyoung Kim, Sohyeon Kim, Jinhyuk Kim, Jaehoon Lee, Seonghak Song, Minyoung Lee, Gunhee Kim
    ACL 2025 Findings
    [paper] [code]

  • DynamicER: Resolving Emerging Mentions to Dynamic Entities for RAG

    Jinyoung Kim, Dayoon Ko, Gunhee Kim
    EMNLP 2024
    [paper] [code]

  • GrowOVER: How Can LLMs Adapt to Growing Real-World Knowledge?

    Dayoon Ko, Jinyoung Kim, Hahyeon Choi, Gunhee Kim
    ACL 2024
    [paper] [code]

Education

  • Seoul National University (Mar. 2018 - Aug. 2024)

    Leave of absence for military service: Jul. 2020 - Jan. 2022
    B.S. in Computer Science and Engineering & B.A. in Economics
    Graduated with Summa Cum Laude

Experiences

  • Vision & Learning Lab, SNU (Sep. 2023 - Present)

    Research Intern

    • Conducted research on evolving knowledge and retrieval-augmented generation
    • Published 3 papers in top-tier conferences
  • CLOVA Voice & Avatar Team, NAVER (Jan. 2023 - Feb. 2023)

    Machine Learning Researcher

    • Topic: Unified Accent Estimation for Speech Synthesis
    • Achieved 7.8% improvement in Accent Phrase (AP) prediction accuracy by unifying estimation for AP and Accent Nucleus (AN) boundaries
    • Designed and implemented novel AN decoder framework to address challenges in the long-tail distribution of accent estimation
  • Music & Audio Research Group, SNU (Jul. 2022 - Aug. 2022)

    Research Intern

    • Conducted research on personalized symbolic music generation
    • Developed contrastive learning-based encoder and holistic frameworks for emotion and style conditioning in music generation

Leadership Experiences