Joohyung Yun

Hi! I'm Joohyung Yun, a 3rd year integrated M.S./Ph.D. student in Computer Science at POSTECH, advised by Professor Wook-Shin Han in the Data Systems Lab. My research sits at the intersection of Natural Language Processing and Information Retrieval, with a focus on Retrieval-Augmented Generation (RAG) for complex, real-world documents.

I'm particularly interested in multimodal document RAG: collections that mix text, tables, and images. My recent projects explore multihop reasoning across these modalities and how to combine retrieval with LLM reasoning effectively. This includes late-interaction retrieval over structured components and multi-granular fusion strategies that blend table–text evidence with LLM inference.

Before turning to RAG, I worked on efficient schema discovery from JSON documents, which led to a first-author publication at PVLDB. I completed my B.S. at POSTECH summa cum laude and previously spent a summer as a full-stack developer at SK hynix.

Contact: jhyun@dblab.postech.ac.kr · joohyung00@postech.ac.kr

Research Focus

I'm currently working on methods and systems for:

• Multimodal & multihop retrieval over documents composed of text, tables, and images
• RAG architectures for reliable QA over multimodal documents

News

Publications

• Conference
  🌸 LILaC: Late Interacting in Layered Component Graph for Open-domain Multimodal Multihop Retrieval
  Yun, J., Lee, D., Han, W.
  EMNLP, 2025.
• Conference
  ☀️ HELIOS: Harmonizing Early Fusion, Late Fusion, and LLM Reasoning for Multi-Granular Table-Text Retrieval
  Park, S., Yun, J., Lee, J., Han, W.
  ACL, 2025.
• Workshop
  🏆 KDD Cup Meta CRAG 2024 Technical Report: Three-Step Question-Answering Framework
  Park, S., Seok, J., Lee, J., Yun, J., Lee, W.
  KDD Cup Workshop on Retrieval-Augmented Generation, 2024.
• Journal
  🧩 ReCG: Bottom-Up JSON Schema Discovery Using a Repetitive Cluster-and-Generalize Framework
  Yun, J., Tak, B., Han, W.
  PVLDB, 2024.