| 2025 | AAAI | Distribution-Level Feature Distancing for Machine Unlearning: Towards a Better Trade-off Between Model Utility and Forgetting. | Dasol Choi, Dongbin Na |
| 2024 | CVPR | 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 |
| 2024 | CVPR | DMR: Disentangling Marginal Representations for Out-of-Distribution Detection. | Dasol Choi, Dongbin Na |
| 2024 | ECCV | Self-Accumulative Vision Transformer for Bone Age Assessment Using the Sauvegrain Method. | Hongjun Choi, Dongbin Na, Kyungjin Cho, Byunguk Bae, Seo Taek Kong, Hyunjoon Ahn, Sungchul Choi, Jaeyoung Kim |
| 2024 | WACV | HOD: New Harmful Object Detection Benchmarks for Robust Surveillance. | Eungyeom Ha, Heemook Kim, Dongbin Na |
| 2023 | AAAI | Key Feature Replacement of In-Distribution Samples for Out-of-Distribution Detection. | Jaeyoung Kim, Seo Taek Kong, Dongbin Na, Kyu-Hwan Jung |
| 2023 | ACL | Pseudo Outlier Exposure for Out-of-Distribution Detection using Pretrained Transformers. | Jaeyoung Kim, Kyuheon Jung, Dongbin Na, Sion Jang, Eunbin Park, Sungchul Choi |
| 2023 | EACL | Bag of Tricks for In-Distribution Calibration of Pretrained Transformers. | Jaeyoung Kim, Dongbin Na, Sungchul Choi, Sungbin Lim |
| 2022 | ECCV | Unrestricted Black-Box Adversarial Attack Using GAN with Limited Queries. | Dongbin Na, Sangwoo Ji, Jong Kim |
| 2020 | WISA | CAPTCHAs Are Still in Danger: An Efficient Scheme to Bypass Adversarial CAPTCHAs. | Dongbin Na, Namgyu Park, Sangwoo Ji, Jong Kim |