| 2025 | ICCV | Target Bias Is All You Need: Zero-Shot Debiasing of Vision-Language Models With Bias Corpus. | Taeuk Jang, Hoin Jung, Xiaoqian Wang |
| 2025 | ICML | On the Alignment between Fairness and Accuracy: from the Perspective of Adversarial Robustness. | Junyi Chai, Taeuk Jang, Jing Gao, Xiaoqian Wang |
| 2024 | AAAI | Adversarial Fairness Network. | Taeuk Jang, Xiaoqian Wang, Heng Huang |
| 2024 | AISTATS | Achieving Fairness through Separability: A Unified Framework for Fair Representation Learning. | Taeuk Jang, Hongchang Gao, Pengyi Shi, Xiaoqian Wang |
| 2024 | CVPR | FADES: Fair Disentanglement with Sensitive Relevance. | Taeuk Jang, Xiaoqian Wang |
| 2023 | CVPR | Difficulty-Based Sampling for Debiased Contrastive Representation Learning. | Taeuk Jang, Xiaoqian Wang |
| 2022 | AAAI | Group-Aware Threshold Adaptation for Fair Classification. | Taeuk Jang, Pengyi Shi, Xiaoqian Wang |
| 2021 | AAAI | Constructing a Fair Classifier with Generated Fair Data. | Taeuk Jang, Feng Zheng, Xiaoqian Wang |
| 2006 | ICCSA | A Study on the Transportation Period of the EPG Data Specification in Terrestrial DMB. | Minju Cho, Jun Hwang, Gyung-Leen Park, Junguk Kim, Taeuk Jang, Juhyun Oh, Young Seok Chae |