A Study of Parameter Efficient Fine-tuning by Learning to Efficiently Fine-Tune. - Taha Ceritli; Savas Özkan; Jeongwon Min; Eunchung Noh; Cho Min; Mete Ozay (EMNLP (Findings), 2024)

Accurate Scene Text Recognition with Efficient Model Scaling and Cloze Self-Distillation. - Andrea Maracani; Savas Özkan; Sijun Cho; Hyowon Kim; Eunchung Noh; Jeongwon Min; Cho Jung Min; Dookun Park; Mete Ozay (CVPR, 2025)

A Study of Improving The Privacy-Utility Trade-off of Task-specific Models with Learnable Privacy. - Savas Özkan; Taha Ceritli; Jeongwon Min; Eunchung Noh; Jung Min Cho; Dookun Park; Mete Ozay (ICASSP, 2025)

Hyper-Refinement for Low-Rank Adaptation. - Savas Özkan; Taha Ceritli; Jeongwon Min; Eunchung Noh; Jung Min Cho; Dookun Park; Mete Ozay (ICASSP, 2025)

Efficient and Accurate Scene Text Recognition with Cascaded-Transformers. - Savas Özkan; Andrea Maracani; Mete Ozay; Hyowon Kim; Sijun Cho; Eunchung Noh; Jeongwon Min; Jung Min Cho (MMSys, 2025)

Unlocking the Value of Decentralized Data: A Federated Dual Learning Approach for Model Aggregation. - Junyi Zhu 002; Ruicong Yao; Taha Ceritli; Savas Özkan; Matthew B. Blaschko; Eunchung Noh; Jeongwon Min; Cho Jung Min; Mete Ozay (CoRR, 2025)