Jun-Hyung Park

Postdoc Researcher

BK21 FOUR R&E Center for Artificial Intelligence

Korea University

I am a postdoc researcher in BK21 FOUR R&E Center for Artificial Intelligence at Korea University. I have obtained my Ph.D. in Computer Science and Engineering from Korea University, advised by Prof. SangKeun Lee. I received B.S. in Computer Science and Engineering from Korea University.

My primary research lies in the area of natural language processing and efficient AI:

  • Commonsense Reasoning: Improving the commonsense reasoning capabilities of pre-trained models including language models and multi-modal transformers. Interested in augmenting the models with (implicit) commonsense knowledge by incorporating knowledge graphs and retrieving texts.
  • Language Models: Improving the various aspects of language models including effectiveness, efficiency, diversity, multilinguality, etc. Addressing any pipeline of language model development, ranging from pre-training to inference.
  • Model Compression: Compressing and accelerating pre-trained models for efficient inference, such as network pruning, quantization, and knowledge distillation.

Education

  • Korea University

    Ph.D. in Computer Science and Engineering
    Adviser: Prof. SangKeun Lee
    Mar 2018 - Feb 2023

  • Korea University

    B.S. in Computer Science and Engineering
    Mar 2014 - Feb 2018

Experience

  • BK21 FOUR R&E Center for Artificial Intelligence, Korea University

    Postdoc researcher
    Mar 2023 - Present

Publications

2024

  • Coconut: Contextualized Commonsense Unified Transformers for Graph-Based Commonsense Augmentation of Language Models

    Jun-Hyung Park, Mingyu Lee, Junho Kim, and SangKeun Lee
    ACL 2024 Under Review

  • Let’s Combine KOPS: Phoneme-Guided Korean Out-of-Vocabulary Processing System

    Nayeon Kim, Eojin Jeon, Jun-Hyung Park, Mingyu Kim, and SangKeun Lee
    ACL 2024 Under Review

2023

  • DIVE: Towards Descriptive and Diverse Visual Commonsense Generation

    Jun-Hyung Park*, Hyuntae Park*, Youjin Kang, Eojin Jeon, and SangKeun Lee
    Proceedings of EMNLP 2023

  • Leap-of-Thought: Accelerating Transformers via Dynamic Token Routing

    Yeachan Kim, Junho Kim, Jun-Hyung Park, Mingyu Lee, and SangKeun Lee
    Proceedings of EMNLP 2023

  • SMoP: Towards Efficient and Effective Prompt Tuning with Sparse Mixture-of-Prompts

    Joon-Young Choi, Junho Kim, Jun-Hyung Park, Wing-Lam Mok, and SangKeun Lee
    Proceedings of EMNLP 2023

  • Client-Customized Adaptation for Parameter-Efficient Federated Learning

    Yeachan Kim*, Junho Kim*, Wing-Lam Mok, Jun-Hyung Park and SangKeun Lee
    Findings of ACL 2023

  • Dynamic Structure Pruning for Compressing CNNs

    Jun-Hyung Park, Yeachan Kim, Junho Kim, Joon-Young Choi, and SangKeun Lee
    Proceedings of AAAI 2023

2022

  • Break it Down into BTS: Basic, Tiniest Subword Units for Korean

    Jun-Hyung Park*, Nayeon Kim*, Joon-Young Choi, Eojin Jeon, Youjin Kang, and SangKeun Lee
    Proceedings of EMNLP 2022

  • Tutoring Helps Students Learn Better: Improving Knowledge Distillation for BERT with Tutor Network

    Jun-Hyung Park*, Junho Kim*, Mingyu Lee, Wing-Lam Mok, Joon-Young Choi, and SangKeun Lee
    Proceedings of EMNLP 2022

  • Efficient Pre-training of Masked Language Model via Concept-based Curriculum Masking

    Jun-Hyung Park*, Mingyu Lee*, Junho Kim, Kang-Min Kim, and SangKeun Lee
    Proceedings of EMNLP 2022

  • Quantized Sparse Training: A Unified Trainable Framework for Joint Pruning and Quantization of DNNs

    Jun-Hyung Park, Kang-Min Kim, and SangKeun Lee
    ACM TECS Volume 21, Issue 5

  • Learning from Missing Relations: Contrastive Learning with Commonsense Knowledge Graphs for Commonsense Inference

    Jun-Hyung Park*, Yong-Ho Jung*, Joon-Young Choi, Mingyu Lee, Junho Kim, Kang-Min Kim, and SangKeun Lee
    Findings of ACL 2022

  • Examining the Impact of Adaptive Convolution on Natural Language Understanding

    Jun-Hyung Park, Byung-Ju Choi, and SangKeun Lee
    ESWA Volume 189

2021

  • KOAS: Korean Text Offensiveness Analysis System

    San-Hee Park*, Kang-Min Kim*, Seonhee Cho*, Jun-Hyung Park, Hyuntae Park, Hyuna Kim, Seongwon Chung, and SangKeun Lee
    Proceedings of EMNLP 2021 (Demo)

2020

  • Multi-pretraining for Large-scale Text Classification

    Kang-Min Kim, Bumsu Hyeon, Yeachan Kim, Jun-Hyung Park, and SangKeun Lee
    Findings of EMNLP 2020

2019

  • meChat: In-device Conversational Photo Sharing Service (demo)

    Jungho Lee, Woo-Jong Ryu, Yoonjoo Ahn, Song-Eun Lee, Kang-Min Kim, Jun-Hyung Park, SangKeun Lee
    Proceedings of MobiSys 2019

  • Adaptive Convolution for Text Classification

    Byung-Ju Choi, Jun-Hyung Park, and SangKeun Lee
    Proceedings of NAACL 2019

2018

  • meChat: In-Device Personal Assistant for Conversational Photo Sharing

    Kang-Min Kim*, Woo-Jong Ryu*, Jun-Hyung Park, SangKeun Lee
    IEEE IC Volume 23, Issue 2

Teaching

  • DFE624 Introduction to Data Science in Python

    Instructor
    Fall 2023 at Korea University

  • DFE611 Modern Information Retrieval Techniques

    Instructor
    Spring 2023 at Korea University

Service

  • Area Chair

    • ACL (2024)
  • Program Committee

    • ACL (2023)
    • AAAI (2023, 2024)
    • EMNLP (2022, 2023)
    • NAACL (2024)
    • IEEE Transactions on Neural Networks and Learning Systems (2024)
    • International Journal of Machine Learning and Cybernetics (2024)