FedPara: Low-rank Hadamard Product Parameterization for Efficient Federated Learning. - Nam Hyeon-Woo; Moon Ye-Bin; Tae-Hyun Oh (CoRR, 2021)

FedPara: Low-rank Hadamard Product for Communication-Efficient Federated Learning. - Nam Hyeon-Woo; Moon Ye-Bin; Tae-Hyun Oh (ICLR, 2022)

Scratching Visual Transformer's Back with Uniform Attention. - Nam Hyeon-Woo; Kim Yu-Ji; Byeongho Heo; Dongyoon Han; Seong Joon Oh; Tae-Hyun Oh (ICCV, 2023)

DFlow: Learning to Synthesize Better Optical Flow Datasets via a Differentiable Pipeline. - Byung-Ki Kwon; Nam Hyeon-Woo; Ji-Yun Kim; Tae-Hyun Oh (ICLR, 2023)

Exploiting Synthetic Data for Data Imbalance Problems: Baselines from a Data Perspective. - Moon Ye-Bin; Nam Hyeon-Woo; Wonseok Choi 001; Nayeong Kim; Suha Kwak; Tae-Hyun Oh (CoRR, 2023)

BEAF: Observing BEfore-AFter Changes to Evaluate Hallucination in Vision-Language Models. - Moon Ye-Bin; Nam Hyeon-Woo; Wonseok Choi 001; Tae-Hyun Oh (ECCV (11), 2024)

SYNAuG: Exploiting synthetic data for data imbalance problems. - Moon Ye-Bin; Nam Hyeon-Woo; Won-Seok Choi 001; Nayeong Kim; Suha Kwak; Tae-Hyun Oh (Pattern Recognit. Lett., 2025)

VLM's Eye Examination: Instruct and Inspect Visual Competency of Vision Language Models. - Nam Hyeon-Woo; Moon Ye-Bin; Wonseok Choi 001; Lee Hyun; Tae-Hyun Oh (Trans. Mach. Learn. Res., 2025)