Cheonbok Park

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 28

Top Topics

Visual Analytics

Document Classification

Convolutional Neural Networks

Top Venues

Publications

Hyuhng Joon Kim, Youna Kim, Cheonbok Park, Junyeob Kim, Choonghyun Park, Kang Min Yoo, Sang-goo Lee, Taeuk Kim
Aligning Language Models to Explicitly Handle Ambiguity. CoRR (2024)
Guijin Son, Hanwool Lee, Sungdong Kim, Seungone Kim, Niklas Muennighoff, Taekyoon Choi, Cheonbok Park, Kang Min Yoo, Stella Biderman
KMMLU: Measuring Massive Multitask Language Understanding in Korean. CoRR (2024)
Chung Park, Junui Hong, Cheonbok Park, Taesan Kim, Minsung Choi, Jaegul Choo
PASTA: PArallel Spatio-Temporal Attention with spatial auto-correlation gating for fine-grained crowd flow prediction. CoRR (2023)
Seungmin Jin, Hyunwook Lee, Cheonbok Park, Hyeshin Chu, Yunwon Tae, Jaegul Choo, Sungahn Ko
A Visual Analytics System for Improving Attention-based Traffic Forecasting Models. IEEE Trans. Vis. Comput. Graph. 29 (1) (2023)
Yujin Baek, Koanho Lee, Dayeon Ki, Cheonbok Park, Hyoung-Gyu Lee, Jaegul Choo
Towards Accurate Translation via Semantically Appropriate Application of Lexical Constraints. ACL (Findings) (2023)
Jihyeon Lee, Taehee Kim, Yunwon Tae, Cheonbok Park, Jaegul Choo
PePe: Personalized Post-editing Model utilizing User-generated Post-edits. EACL (Findings) (2023)
Yujin Baek, Koanho Lee, Dayeon Ki, Hyoung-Gyu Lee, Cheonbok Park, Jaegul Choo
Towards Accurate Translation via Semantically Appropriate Application of Lexical Constraints. CoRR (2023)
Chung Park, Junui Hong, Cheonbok Park, Taesan Kim, Minsung Choi, Jaegul Choo
PASTA: PArallel Spatio-Temporal Attention with Spatial Auto-Correlation Gating for Fine-Grained Crowd Flow Prediction. PAKDD (1) (2022)
Jihyeon Lee, Taehee Kim, Yunwon Tae, Cheonbok Park, Jaegul Choo
PePe: Personalized Post-editing Model utilizing User-generated Post-edits. CoRR (2022)
Jiyoung Lee, Hantae Kim, Hyunchang Cho, Edward Choi, Cheonbok Park
Specializing Multi-domain NMT via Penalizing Low Mutual Information. EMNLP (2022)
Cheonbok Park, Hantae Kim, Ioan Calapodescu, Hyunchang Cho, Vassilina Nikoulina
DaLC: Domain Adaptation Learning Curve Prediction for Neural Machine Translation. CoRR (2022)
Daejin Kim, Youngin Cho, Dongmin Kim, Cheonbok Park, Jaegul Choo
Residual Correction in Real-Time Traffic Forecasting. CIKM (2022)
Jiyoung Lee, Hantae Kim, Hyunchang Cho, Edward Choi, Cheonbok Park
Specializing Multi-domain NMT via Penalizing Low Mutual Information. CoRR (2022)
Seungmin Jin, Hyunwook Lee, Cheonbok Park, Hyeshin Chu, Yunwon Tae, Jaegul Choo, Sungahn Ko
A Visual Analytics System for Improving Attention-based Traffic Forecasting Models. CoRR (2022)
Taesung Kim, Jinhee Kim, Yunwon Tae, Cheonbok Park, Jang-Ho Choi, Jaegul Choo
Reversible Instance Normalization for Accurate Time-Series Forecasting against Distribution Shift. ICLR (2022)
Cheonbok Park, Hantae Kim, Ioan Calapodescu, Hyunchang Cho, Vassilina Nikoulina
DaLC: Domain Adaptation Learning Curve Prediction for Neural Machine Translation. ACL (Findings) (2022)
Daejin Kim, Youngin Cho, Dongmin Kim, Cheonbok Park, Jaegul Choo
Residual Correction in Real-Time Traffic Forecasting. CoRR (2022)
Cheonbok Park, Soyoung Yang, Inyoup Na, Sunghyo Chung, Sungbok Shin, Bum Chul Kwon, Deokgun Park, Jaegul Choo
VATUN: Visual Analytics for Testing and Understanding Convolutional Neural Networks. EuroVis (Short Papers) (2021)
Cheonbok Park, Yunwon Tae, Taehee Kim, Soyoung Yang, Mohammad Azam Khan, Lucy Park, Jaegul Choo
Unsupervised Neural Machine Translation for Low-Resource Domains via Meta-Learning. ACL/IJCNLP (1) (2021)
Hyunwook Lee, Cheonbok Park, Seungmin Jin, Hyeshin Chu, Jaegul Choo, Sungahn Ko
An Empirical Experiment on Deep Learning Models for Predicting Traffic Data. ICDE (2021)
Hyunwook Lee, Cheonbok Park, Seungmin Jin, Hyeshin Chu, Jaegul Choo, Sungahn Ko
An Empirical Experiment on Deep Learning Models for Predicting Traffic Data. CoRR (2021)
Cheonbok Park, Chunggi Lee, Hyojin Bahng, Yunwon Tae, Seungmin Jin, Kihwan Kim, Sungahn Ko, Jaegul Choo
ST-GRAT: A Novel Spatio-temporal Graph Attention Networks for Accurately Forecasting Dynamically Changing Road Speed. CIKM (2020)
Yunwon Tae, Cheonbok Park, Taehee Kim, Soyoung Yang, Mohammad Azam Khan, Eunjeong Park, Tao Qin, Jaegul Choo
Meta-Learning for Low-Resource Unsupervised Neural MachineTranslation. CoRR (2020)
Cheonbok Park, Inyoup Na, Yongjang Jo, Sungbok Shin, Jaehyo Yoo, Bum Chul Kwon, Jian Zhao, Hyungjong Noh, Yeonsoo Lee, Jaegul Choo
SANVis: Visual Analytics for Understanding Self-Attention Networks. CoRR (2019)
Cheonbok Park, Chunggi Lee, Hyojin Bahng, Taeyun won, Kihwan Kim, Seungmin Jin, Sungahn Ko, Jaegul Choo
STGRAT: A Spatio-Temporal Graph Attention Network for Traffic Forecasting. CoRR (2019)
Wooyoung Kim, Wonwoong Cho, Jangho Choi, Jiyong Kim, Cheonbok Park, Jaegul Choo
A Comparison of the Effects of Data Imputation Methods on Model Performance. ICACT (2019)
Minsuk Choi, Cheonbok Park, Soyoung Yang, Yonggyu Kim, Jaegul Choo, Sungsoo Ray Hong
AILA: Attentive Interactive Labeling Assistant for Document Classification through Attention-Based Deep Neural Networks. CHI (2019)
Cheonbok Park, Jaegul Choo, Inyoup Na, Yongjang Jo, Sungbok Shin, Jaehyo Yoo, Bum Chul Kwon, Jian Zhao, Hyungjong Noh, Yeonsoo Lee
SANVis: Visual Analytics for Understanding Self-Attention Networks. IEEE VIS (Short Papers) (2019)