Eunchung Noh

11 papers A* 2A 1Misc 2Journal 5Unranked 1
YearRankTypeTitle / Venue / Authors
2026 A* conf
Let the Void Be Void: Robust Open-Set Semi-Supervised Learning via Selective Non-Alignment.
AAAI
You Rim Choi, Subeom Park, Seojun Heo, Eunchung Noh, Hyung-Sin Kim
2025 Misc conf
A Study of Improving The Privacy-Utility Trade-off of Task-specific Models with Learnable Privacy.
ICASSP
Savas Özkan, Taha Ceritli, Jeongwon Min, Eunchung Noh, Jung Min Cho, Dookun Park, Mete Ozay
2025 A* conf
Accurate Scene Text Recognition with Efficient Model Scaling and Cloze Self-Distillation.
CVPR
Andrea Maracani, Savas Özkan, Sijun Cho, Hyowon Kim, Eunchung Noh, Jeongwon Min, Cho Jung Min, Dookun Park, Mete Ozay
2025 J jnl
Accurate Scene Text Recognition with Efficient Model Scaling and Cloze Self-Distillation.
CoRR
Andrea Maracani, Savas Özkan, Sijun Cho, Hyowon Kim, Eunchung Noh, Jeongwon Min, Cho Jung Min, Dookun Park, Mete Ozay
2025 A conf
Efficient and Accurate Scene Text Recognition with Cascaded-Transformers.
MMSys
Savas Özkan, Andrea Maracani, Mete Ozay, Hyowon Kim, Sijun Cho, Eunchung Noh, Jeongwon Min, Jung Min Cho
2025 J jnl
Efficient and Accurate Scene Text Recognition with Cascaded-Transformers.
CoRR
Savas Özkan, Andrea Maracani, Hyowon Kim, Sijun Cho, Eunchung Noh, Jeongwon Min, Jung Min Cho, Mete Ozay
2025 Misc conf
Hyper-Refinement for Low-Rank Adaptation.
ICASSP
Savas Özkan, Taha Ceritli, Jeongwon Min, Eunchung Noh, Jung Min Cho, Dookun Park, Mete Ozay
2025 J jnl
The Others: Naturally Isolating Out-of-Distribution Samples for Robust Open-Set Semi-Supervised Learning.
CoRR
You Rim Choi, Subeom Park, Seojun Heo, Eunchung Noh, Hyung-Sin Kim
2025 J jnl
Toward Responsible Federated Large Language Models: Leveraging a Safety Filter and Constitutional AI.
CoRR
Eunchung Noh, Jeonghun Baek
2025 J jnl
Unlocking the Value of Decentralized Data: A Federated Dual Learning Approach for Model Aggregation.
CoRR
Junyi Zhu, Ruicong Yao, Taha Ceritli, Savas Özkan, Matthew B. Blaschko, Eunchung Noh, Jeongwon Min, Cho Jung Min, Mete Ozay
2024 — conf
A Study of Parameter Efficient Fine-tuning by Learning to Efficiently Fine-Tune.
EMNLP (Findings)
Taha Ceritli, Savas Özkan, Jeongwon Min, Eunchung Noh, Cho Min, Mete Ozay