[C] Conference, [J] Journal, [W] Workshopt, [P] Preprint, [*] Equal contribution, [^] Equal correspondence
[C] Conference, [J] Journal, [W] Workshopt, [P] Preprint, [*] Equal contribution, [^] Equal correspondence
2025
[J1]FedDr+: Stabilizing Dot-Regression with Global Feature Distillation for Federated Learning (π)
Seongyoon Kim, Minchan Jeong, Sungnyun Kim, Sungwoo Cho, Sumyeong Ahn^, and Se-Young Yun^
TMLR
2024
[P6]ConDS: Context Distribution Shift for Robust In-Context Learning
Shuyang Yu et al.
Preprint
[P5]Distribured In-Context Learning Under Non-IID Among Clients
Siqi Liang*, Sumyeong Ahn*, Jiayu Zhou
Preprint
[P4]Prompt Learning with Noisy Labels
Sumyeong Ahn et al.
Preprint
[P3]ORBIS: Open Dataset Can Rescue You From Dataset Bias Problem
Sumyeong Ahn, Se-Young Yun
Preprint
[P2]Large Language Models In Medical Term Classification And Unexpected Misalignment Between Response and Reasoning
Xiaodan Zhang, Sandeep Vemulapalli, Nabasmita Talukdar, Sumyeong Ahn, Jiankun Wang, Han Meng, Sardar Mehtab Bin Murtaza, Aakash Ajay Dave, Dmitry Leshchiner, Dimitri F Joseph, Martin Witteveen-Lane, Dave Chesla, Jiayu Zhou, Bin Chen
Preprint
[P1]Augmented Risk Prediction for Onset of Alzheimerβs Disease from Electronic Health Records with Large Language Models
Jiankun Wang, Sumyeong Ahn, Taykhoom Dalal, Xiaodan Zhang, Weishen Pan, Qiannan Zhang, Bin Chen, Hiroko H Dodge, Fei Wang, Jiayu Zhou
Preprint
[W7] VaCoDe: Visual Augmented Contrastive Learning (π)
Sihyeon Kim, Boryeong Cho, Sangmin Bae, Sumyeong Ahn^, Se-Young Yun^
ICML-W 2024
[W6] FedDr+: Stabilizing Dot-Regression with Global Feature Distillation for Federated Learning (π)
Seongyoon Kim, Minchan Jeong, Sungnyun Kim, Sungwoo Cho, Sumyeong Ahn^, Se-Young Yun^
KDD-W 2024
[C11] Comparison of Prompt Engineering and Fine-Tuning Strategies in Large Language Models in the Classification of Clinical Notes (π)
Xiaodan Zhang, Nabasmita Talukdar, Sandeep Vemulapalli, Sumyeong Ahn, Jiankun Wang, Han Meng, Sardar Mehtab Bin Murtaza, Dmitry Leshchiner, Aakash Ajay Dave, Dimitri F Joseph, Martin Witteveen-Lane, Dave Chesla, Jiayu Zhou, Bin Chen
AMIA 2024
[C10] Fine-Tuning Pre-trained Models for Robustness Under Noisy Labels (π)
Sumyeong Ahn,Sihyeon Kim, Jongwoo Ko, Se-Young Yun
IJCAI 2024
[C9] Active Prompt Learning in Vision Language Models (π)
Jihwan Bang, Sumyeong Ahn, Jae-Gil Lee
CVPR 2024
2023
[C8] NASH: A Simple Unified Framework of Structured Pruning for Accelerating Encoder-Decoder Language Models (π)
Jongwoo Ko*, Seungjoon Park*, Yujin Kim, Du-Seong Chang, Euijai Ahn, Sumyeong Ahn^, Se-Young Yun^
EMNLP 2023 (Findings)
[C7] Denoising After Entropy-based Debiasing: A Robust Training Method for Dataset Bias with Noisy Labels (π)
Sumyeong Ahn, Se-Young Yun
AAAI 2023
[C6/W3] CUDA: Curriculum of Data Augmentation for Long-tailed Recognition (π)
Sumyeong Ahn*, Jongwoo Ko*, Se-Young Yun
ICLR 2023
[C5/W2] Mitigating Dataset Bias By Using Per-sample Gradient (π)
Sumyeong Ahn*, Seongyoon Kim*, Se-Young Yun
ICLR 2023
[W1] Efficient Utilization of Pre-trained Model for Learning with Noisy Labels (π)
Jongwoo Ko*, Sumyeong Ahn*, Se-Young Yun
ICLR-W 2023
Before 2022
[C4] Client Sampling Algorithm in Federated Learning via Combinatorial Averaging and Multi-armed Bandits (π)
Sangmin Bae, Taehyeon Kim, Sumyeong Ahn, Sangmook Kim, Jongwoo Ko, Se-Young Yun
KIISE 2022
[C3] Neuro-DCF: Design of Wireless MAC via Multi-Agent Reinforcement Learning Approach (π)
Sangwoo Moon, Sumyeong Ahn, Kyunghwan Son, Jinwoo Park, Yung Yi
MobiHoc 2021
[C2] Enlarging Discriminative Power by Adding an Extra Class in Unsupervised Domain Adaptation (π)
Hai H Tran, Sumyeong Ahn, Taeyoung Lee, Yung Yi
ICPR 2021
[C1] Multi-armed Bandit with Additional Observations (π)
Donggyu Yun, Sumyeong Ahn, Alexandre Proutiere, Jinwoo Shin, Yung Yi
SIGMETRICS 2018