Cheonbok Park

I am a research scientist at Papago, NAVER Corp. My research interest has focused on machine learning for natural language processing and the spatio-temporal modeling. I am also interested in visualizing machine learning models and Human-in-the-loop Machine learning. I received B.S and M.S in Computer Science at Korea University. During M.S degree, I was advised by professor Jaegul Choo.


Specializing Multi-domain NMT via Penalizing Low Mutual Information
Jiyoung Lee, Hantae Kim, Hyunchang Cho, Edward Cho, and Cheonbok Park
Empirical Methods in Natural Language Processing (EMNLP), Short Paper, 2022

Residual Correction in Real-Time Traffic Forecasting
Daejin Kim,* Youngin Cho,* Dongmin Kim, Cheonbok Park, and Jaegul Choo (*: equal contributions)
ACM International Conference on Information and Knowledge Management (CIKM), 2022.

A Visual Analytics System for Improving Traffic Forecasting Models
Seungmin Jin, Hyunwook Lee, Cheonbok Park, Hyeshin Chu, Yunwon Tae, Jaegul Choo , and Sungahn Ko
IEEE Trans. on Visualization and Computer Graphics (TVCG), 2023 (Proc. IEEE VIS’22)

DaLC: Domain Adaptation Learning Curve Prediction for Neural Machine Translation
Cheonbok Park, Hantae Kim, Ioan Calapodescu, Hyunchang Cho, and Vassilina Nikoulina
Meeting of the Association for Computational Linguistics (ACL), Findings Long Paper, 2022

Reversible Instance Normalization for Accurate Time-Series Forecasting against Distribution Shift
Taesung Kim,* Jinhee Kim,* Yunwon Tae, Cheonbok Park, Jang-Ho Choi, and Jaegul Choo (*: equal contributions)
International Conference on Learning Representations (ICLR), 2022.

PASTA : Parallel Spatio-Temporal Attention with Spatial Auto-Correlation Gating for Fine-Grained Crowd Flows Prediction
Chung Park, Junui Hong, Cheonbok Park, Taesan Kim, Minsung Choi, and Jaegul Choo
Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2022.

Meta-Learning for Low-Resource Unsupervised Neural Machine Translation
Cheombok Park*, Yunwon Tae*, TaeHee Kim, Soyoung Yang, Mohammad Azam Khan, Lucy Park and Jaegul Choo (* indicates equal contribution)
Meeting of the Association for Computational Linguistics (ACL), Long Paper, 2021

VATUN: Visual Analytics for Testing and Understanding Convolutional Neural Networks
Cheonbok Park*, Soyoung Yang*, Inyoup Na*, Sunghyo Chung, Sungbok Shin, Bum Chul Kwon, Deokgun Park, and Jaegul Choo (* indicates equal contribution)
EG/VGTC Conference on Visualization (EuroVis), Short Paper, 2021

Empirical Experiment on Deep Learning Models for Predicting Traffic Data
Hyunwook Lee, Cheonbok Park, Seungmin Jin, Hyeshin Chu, Jaegul Choo, and Sungahn Ko IEEE International Conference on Data Engineering (ICDE), Short Paper, 2021.

ST-GRAT: A Novel Spatio-temporal Graph Attention Network for Accurately Forecasting Dynamically Changing Road Speed
Cheonbok Park, Chunggi Lee, Hyojin Bahng, Yunwon Tae, Seungmin Jin, Kihwan Kim, Sungahn Ko, and Jaegul Choo ACM International Conference on Information and Knowledge Management (CIKM), 2020

SANVis: Visual Analytics for Understanding Self-Attention Networks
Cheonbok Park, Inyoup Na, Yongjang Jo, Sungbok Shin, Jaehyo Yoo, Bum Chul Kwon, Jian Zhao, Hyungjong Noh, Yeonsoo Lee, and Jaegul Choo
IEEE VIS, Short Paper, 2019, Vancouver, Canada.

AILA: Attentive Interactive Labeling Assistant for Document Classification through Attention-based Deep Neural Networks
Minsuk Choi, Cheonbok Park, Soyoung Yang, Yonggyu Kim, Jaegul Choo, and Sungsoo (Ray) Hong
ACM CHI Conference on Human Factors in Computing Systems (CHI), 2019, Glasgow, UK.

A Comparison of the Effects of Data Imputation Methods on Model Performance
Wooyoung Kim*, Wonwoong Cho*, Jangho Choi, Jiyong Kim, Cheonbok Park, Jaegul Choo (* indicates equal contribution)
IEEE International Conference on Advanced Communications Technology (ICACT), 2019, Pyeongchang, KR.

Real-time UAV sound detection and analysis system
Juhyun Kim, Cheonbok Park, Jinwoo Ahn, Youlim Ko, Junghyun Park, John C. Gallaghe
IEEE Sensors Applications Symposium(SAS), 2017, UK.

ReVACNN: Steering Real-Time Visual Analytics for Convolutional Neural Network
Sunghyo Chung, Cheonbok Park, Sangho Suh, Kyeongpil Kang, Jaegul Choo, and Bum Chul Kwon
In NeurIPS Workshop on Future of Interactive Learning Machines(NIPS-FILM), 2016.

ReVACNN: Real-Time Visual Analytics for Convolutional Neural Network
Sunghyo Chung, Sangho Suh, Cheonbok Park, Kyeongpil Kang, Jaegul Choo, and Bum Chul Kwon
ACM SIGKDD Workshop on Interactive Data Exploration and Analytics (KDD-IDEA), 2016, San Francisco, CA.

Honors and awards

Gold Prize (1st Place) KU Graduate Project Competition, 2017, Korea University.

Republic of Korea Presidential Science Scholarship, 2013-2017, Government of the Republic of Korea
Full-tuition scholarship with stipend for undergraduate studies in CS fields. One of 135 awardees in Korea.