Learning Debiased Representation via Disentangled Feature Augmentation. - Jungsoo Lee; Eungyeup Kim; Juyoung Lee 001; Jihyeon Lee; Jaegul Choo (NeurIPS, 2021)

BiasEnsemble: Revisiting the Importance of Amplifying Bias for Debiasing. - Jungsoo Lee; Jeonghoon Park; Daeyoung Kim; Juyoung Lee 001; Edward Choi 003; Jaegul Choo (CoRR, 2022)

DebiasBench: Benchmark for Fair Comparison of Debiasing in Image Classification. - Jungsoo Lee; Juyoung Lee 001; Sanghun Jung; Jaegul Choo (CoRR, 2022)

Revisiting the Importance of Amplifying Bias for Debiasing. - Jungsoo Lee; Jeonghoon Park; Daeyoung Kim; Juyoung Lee 001; Edward Choi 003; Jaegul Choo (AAAI, 2023)

Enhancing Intrinsic Features for Debiasing via Investigating Class-Discerning Common Attributes in Bias-Contrastive Pair. - Jeonghoon Park; Chaeyeon Chung; Juyoung Lee 001; Jaegul Choo (CoRR, 2024)

Fair Generation without Unfair Distortions: Debiasing Text-To-Image Generation with Entanglement-Free Attention. - Jeonghoon Park; Juyoung Lee 001; Chaeyeon Chung; Jaeseong Lee; Jaegul Choo; Jindong Gu (ICCV, 2025)

Colored-MNIST. - Jungsoo Lee; Eungyeup Kim; Juyoung Lee 001; Jihyeon Lee; Jaegul Choo (IEEE DataPort, 2025)