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research

I am interested in simple, intuitive, and scalable algorithms for teaching large neural networks. I design new algorithms to teach them and build both empirical and theoretical foundations of these algorithms. Recently, I have been studying how to teach safe and knowledgable large language models.

During undergrad, I did research with the Allen Institute for AI on developing scalable ways to build data for training/evaluating vision-language models, e.g., using internet-scale videos to teach vision-grounded dialogue (CHAMPAGNE) and using large language models to create challenging vision-language benchmarks (NormLens, SMILE).

I also worked on research and engineering at a startup (Hyperconnect; acquired by Match Group for $1.7B), solving product-related problems like long-tail classification (PC Softmax & LADE) and building social chatbot products (DRESS, PDP, CORGE, G2R, Attentron) to solve people’s loneliness.

Please see my google scholar or semantic scholar for an up-to-date list.

selected publications

* denotes equal contribution.
  1. EMNLP
    Reading Books is Great, But Not if You Are Driving! Visually Grounded Reasoning about Defeasible Commonsense Norms
    Seungju Han, Junhyeok Kim, Jack Hessel, Liwei Jiang, Jiwan Chung, Yejin Son, Yejin Choi, and Youngjae Yu
    In Conference on Empirical Methods in Natural Language Processing (EMNLP, Oral Presentation) 2023
  2. ICCV
    CHAMPAGNE: Learning Real-world Conversation from Large-Scale Web Videos
    Seungju Han, Jack Hessel, Nouha Dziri, Yejin Choi, and Youngjae Yu
    In International Conference on Computer Vision (ICCV) 2023
  3. EMNLP
    Measuring and Improving Semantic Diversity of Dialogue Generation
    Seungju Han, Beomsu Kim, and Buru Chang
    In Conference on Empirical Methods in Natural Language Processing (EMNLP Findings) 2022
  4. CVPR
    Disentangling Label Distribution for Long-tailed Visual Recognition
    Youngkyu* Hong*,  Seungju Han*, Kwanghee Choi*, Seokjun Seo, Beomsu Kim, and Buru Chang
    In Conference on Computer Vision and Pattern Recognition (CVPR) 2021