Dongbin Na

According to our database, Dongbin Na authored at least 19 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Distribution-Level Feature Distancing for Machine Unlearning: Towards a Better Trade-off Between Model Utility and Forgetting.

Dasol Choi, Dongbin Na

CoRR, 2024

HOD: New Harmful Object Detection Benchmarks for Robust Surveillance.

Eungyeom Ha, Heemook Kim, Dongbin Na

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision Workshops, 2024

DMR: Disentangling Marginal Representations for Out-of-Distribution Detection.

Dasol Choi, Dongbin Na

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

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

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

Towards Reliable AI Model Deployments: Multiple Input Mixup for Out-of-Distribution Detection.

Dasol Choi, Dongbin Na

CoRR, 2023

Towards Machine Unlearning Benchmarks: Forgetting the Personal Identities in Facial Recognition Systems.

Dasol Choi, 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

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

Problem-Solving Guide: Predicting the Algorithm Tags and Difficulty for Competitive Programming Problems.

Juntae Kim, Eunjung Cho, Dongwoo Kim, Dongbin Na

CoRR, 2023

HOD: A Benchmark Dataset for Harmful Object Detection.

Eungyeom Ha, Heemook Kim, Sung Chul Hong, Dongbin Na

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

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

Bag of Tricks for In-Distribution Calibration of Pretrained Transformers.

Jaeyoung Kim, Dongbin Na, Sungchul Choi, Sungbin Lim

Proceedings of the Findings of the Association for Computational Linguistics: EACL 2023, 2023

Pseudo Outlier Exposure for Out-of-Distribution Detection using Pretrained Transformers.

Jaeyoung Kim, Kyuheon Jung, Dongbin Na, Sion Jang, Eunbin Park, Sungchul Choi

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

Key Feature Replacement of In-Distribution Samples for Out-of-Distribution Detection.

Jaeyoung Kim, Seo Taek Kong, Dongbin Na, Kyu-Hwan Jung

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Defending against attacks tailored to transfer learning via feature distancing.

Sangwoo Ji, Namgyu Park, Dongbin Na, Bin Zhu, Jong Kim

Comput. Vis. Image Underst., 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

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Unrestricted Black-Box Adversarial Attack Using GAN with Limited Queries.

Dongbin Na, Sangwoo Ji, Jong Kim

Proceedings of the Computer Vision - ECCV 2022 Workshops, 2022

2020

CAPTCHAs Are Still in Danger: An Efficient Scheme to Bypass Adversarial CAPTCHAs.

Dongbin Na, Namgyu Park, Sangwoo Ji, Jong Kim

Proceedings of the Information Security Applications - 21st International Conference, 2020