Ahn, Sumyeong

13 publications

TMLR 2025 FedDr+: Stabilizing Dot-Regression with Global Feature Distillation for Federated Learning Seongyoon Kim, Minchan Jeong, Sungnyun Kim, Sungwoo Cho, Sumyeong Ahn, Se-Young Yun

TMLR 2025 VSCoDe: Visual-Augmentation Selection for Contrastive Decoding Sihyeon Kim, Boryeong Cho, Sangmin Bae, Sumyeong Ahn, Se-Young Yun

CVPR 2024 Active Prompt Learning in Vision Language Models Jihwan Bang, Sumyeong Ahn, Jae-Gil Lee

IJCAI 2024 Fine-Tuning Pre-Trained Models for Robustness Under Noisy Labels Sumyeong Ahn, Sihyeon Kim, Jongwoo Ko, Se-Young Yun

ICMLW 2024 VACoDe: Visual Augmented Contrastive Decoding Sihyeon Kim, Boryeong Cho, Sangmin Bae, Sumyeong Ahn, Se-Young Yun

ICLR 2023 CUDA: Curriculum of Data Augmentation for Long-Tailed Recognition Sumyeong Ahn, Jongwoo Ko, Se-Young Yun

AAAI 2023 Denoising After Entropy-Based Debiasing a Robust Training Method for Dataset Bias with Noisy Labels Sumyeong Ahn, Se-Young Yun

ICLRW 2023 Efficient Utilization of Pre-Trained Model for Learning with Noisy Labels Jongwoo Ko, Sumyeong Ahn, Se-Young Yun

ICLR 2023 Mitigating Dataset Bias by Using Per-Sample Gradient Sumyeong Ahn, Seongyoon Kim, Se-Young Yun

NeurIPSW 2022 CUDA: Curriculum of Data Augmentation for Long-Tailed Recognition Sumyeong Ahn, Jongwoo Ko, Se-Young Yun

NeurIPSW 2022 CUDA: Curriculum of Data Augmentation for Long-Tailed Recognition Sumyeong Ahn, Jongwoo Ko, Se-Young Yun

NeurIPSW 2022 Mitigating Dataset Bias by Using Per-Sample Gradient Sumyeong Ahn, Seongyoon Kim, Se-Young Yun

NeurIPSW 2022 Mitigating Dataset Bias by Using Per-Sample Gradient Sumyeong Ahn, Seongyoon Kim, Se-Young Yun