CAPTCHAs Are Still in Danger: An Efficient Scheme to Bypass Adversarial CAPTCHAs. - Dongbin Na; Namgyu Park; Sangwoo Ji; Jong Kim 001 (WISA, 2020)

Unrestricted Black-Box Adversarial Attack Using GAN with Limited Queries. - Dongbin Na; Sangwoo Ji; Jong Kim 001 (ECCV Workshops (1), 2022)

A Neural Pre-Conditioning Active Learning Algorithm to Reduce Label Complexity. - Seo Taek Kong; Soomin Jeon; Dongbin Na; Jaewon Lee; Hong-Seok Lee; Kyu-Hwan Jung (NeurIPS, 2022)

Defending against attacks tailored to transfer learning via feature distancing. - Sangwoo Ji; Namgyu Park; Dongbin Na; Bin Zhu 008; Jong Kim 001 (Comput. Vis. Image Underst., 2022)

Key Feature Replacement of In-Distribution Samples for Out-of-Distribution Detection. - Jaeyoung Kim; Seo Taek Kong; Dongbin Na; Kyu-Hwan Jung (AAAI, 2023)

Pseudo Outlier Exposure for Out-of-Distribution Detection using Pretrained Transformers. - Jaeyoung Kim; Kyuheon Jung; Dongbin Na; Sion Jang; Eunbin Park; Sungchul Choi (ACL (Findings), 2023)

Bag of Tricks for In-Distribution Calibration of Pretrained Transformers. - Jaeyoung Kim; Dongbin Na; Sungchul Choi; Sungbin Lim (EACL (Findings), 2023)

Self-accumulative Vision Transformer for Bone Age Assessment Using the Sauvegrain Method. - Hong-Jun Choi; Dongbin Na; Kyungjin Cho; Byunguk Bae; Seo Taek Kong; Hyunjoon An (CoRR, 2023)

Large-Scale Korean Text Dataset for Classifying Biased Speech in Real-World Online Services. - Dasol Choi; Jooyoung Song; Eunsun Lee; Jinwoo Seo; Heejune Park; Dongbin Na (CoRR, 2023)

HOD: A Benchmark Dataset for Harmful Object Detection. - Eungyeom Ha; Heemook Kim; Sung Chul Hong; Dongbin Na (CoRR, 2023)

Problem-Solving Guide: Predicting the Algorithm Tags and Difficulty for Competitive Programming Problems. - Juntae Kim; Eunjung Cho; Dongwoo Kim; Dongbin Na (CoRR, 2023)

New Benchmarks for Asian Facial Recognition Tasks: Face Classification with Large Foundation Models. - Jinwoo Seo; Soora Choi; Eungyeom Ha; Beomjune Kim; Dongbin Na (CoRR, 2023)

A New Korean Text Classification Benchmark for Recognizing the Political Intents in Online Newspapers. - Beomjune Kim; Eunsun Lee; Dongbin Na (CoRR, 2023)

Towards Machine Unlearning Benchmarks: Forgetting the Personal Identities in Facial Recognition Systems. - Dasol Choi; Dongbin Na (CoRR, 2023)

Towards Reliable AI Model Deployments: Multiple Input Mixup for Out-of-Distribution Detection. - Dasol Choi; Dongbin Na (CoRR, 2023)

Towards Efficient Machine Unlearning with Data Augmentation: Guided Loss-Increasing (GLI) to Prevent the Catastrophic Model Utility Drop. - Dasol Choi; Soora Choi; Eunsun Lee; Jinwoo Seo; Dongbin Na (CVPR Workshops, 2024)

DMR: Disentangling Marginal Representations for Out-of-Distribution Detection. - Dasol Choi; Dongbin Na (CVPR Workshops, 2024)

Self-Accumulative Vision Transformer for Bone Age Assessment Using the Sauvegrain Method. - Hong-Jun Choi; Dongbin Na; Kyungjin Cho; Byunguk Bae; Seo Taek Kong; Hyunjoon Ahn; Sungchul Choi; Jaeyoung Kim (ECCV Workshops (19), 2024)

HOD: New Harmful Object Detection Benchmarks for Robust Surveillance. - Eungyeom Ha; Heemook Kim; Dongbin Na (WACV (Workshops), 2024)

Distribution-Level Feature Distancing for Machine Unlearning: Towards a Better Trade-off Between Model Utility and Forgetting. - Dasol Choi; Dongbin Na (AAAI, 2025)