A new method to increase the quality of cardiopulmonary resuscitation in hospital. - Yeongtak Song; Jaehoon Oh; Tae Ho Lim; Youngjoon Chee (EMBC, 2013)

A Feasibility Study of Smartphone-Based Telesonography for Evaluating Cardiac Dynamic Function and Diagnosing Acute Appendicitis with Control of the Image Quality of the Transmitted Videos. - Changsun Kim; Hyunmin Cha; Bo Seung Kang; Hyuk Joong Choi; Tae Ho Lim; Jaehoon Oh (J. Digit. Imaging, 2016)

A Feasibility Study of Telementoring for Identifying the Appendix Using Smartphone-Based Telesonography. - Yoonje Lee; Changsun Kim; Hyuk Joong Choi; Bossng Kang; Jaehoon Oh; Tae Ho Lim (J. Digit. Imaging, 2017)

TED Talk Recommender Using Speech Transcripts. - Jaehoon Oh; Injung Lee; Yeon Seonwoo; Simin Sung; Ilbong Kwon; Jae-Gil Lee 001 (ASONAM, 2018)

Spectrogram-channels u-net: a source separation model viewing each channel as the spectrogram of each source. - Jaehoon Oh; Duyeon Kim; Se-Young Yun (CoRR, 2018)

A pipelined hybrid recommender system for ranking the items on the display. - Jaehoon Oh; Sangmook Kim; Se-Young Yun; Seungwoo Choi; Mun Yong Yi (RecSys Challenge, 2019)

SIPA: A Simple Framework for Efficient Networks. - Gihun Lee; Sangmin Bae; Jaehoon Oh; Se-Young Yun (ICDM (Workshops), 2020)

Does MAML really want feature reuse only? - Jaehoon Oh; Hyungjun Yoo; ChangHwan Kim; Se-Young Yun (CoRR, 2020)

TornadoAggregate: Accurate and Scalable Federated Learning via the Ring-Based Architecture. - Jin-Woo Lee; Jaehoon Oh; Sungsu Lim; Se-Young Yun; Jae-Gil Lee 001 (CoRR, 2020)

Accurate and Fast Federated Learning via IID and Communication-Aware Grouping. - Jin-Woo Lee; Jaehoon Oh; Yooju Shin; Jae-Gil Lee 001; Se-Young Yoon (CoRR, 2020)

BOIL: Towards Representation Change for Few-shot Learning. - Jaehoon Oh; Hyungjun Yoo; ChangHwan Kim; Se-Young Yun (ICLR, 2021)

Comparing Kullback-Leibler Divergence and Mean Squared Error Loss in Knowledge Distillation. - Taehyeon Kim 001; Jaehoon Oh; Nakyil Kim; Sangwook Cho; Se-Young Yun (IJCAI, 2021)

FedBABU: Towards Enhanced Representation for Federated Image Classification. - Jaehoon Oh; Sangmook Kim; Se-Young Yun (CoRR, 2021)

External Validation of Deep Learning Algorithm for Detecting and Visualizing Femoral Neck Fracture Including Displaced and Non-displaced Fracture on Plain X-ray. - Junwon Bae; Sangjoon Yu; Jaehoon Oh; Tae Hyun Kim 006; Jae Ho Chung; Hayoung Byun; Myeong Seong Yoon; Chiwon Ahn; Dong Keon Lee (J. Digit. Imaging, 2021)

ReFine: Re-randomization before Fine-tuning for Cross-domain Few-shot Learning. - Jaehoon Oh; Sungnyun Kim; Namgyu Ho; Jin-Hwa Kim; Hwanjun Song; Se-Young Yun (CIKM, 2022)

Synergy with Translation Artifacts for Training and Inference in Multilingual Tasks. - Jaehoon Oh; Jongwoo Ko; Se-Young Yun (EMNLP, 2022)

FedBABU: Toward Enhanced Representation for Federated Image Classification. - Jaehoon Oh; Sangmook Kim; Se-Young Yun (ICLR, 2022)

Understanding Cross-Domain Few-Shot Learning Based on Domain Similarity and Few-Shot Difficulty. - Jaehoon Oh; Sungnyun Kim; Namgyu Ho; Jin-Hwa Kim; Hwanjun Song; Se-Young Yun (NeurIPS, 2022)

Understanding Cross-Domain Few-Shot Learning: An Experimental Study. - Jaehoon Oh; Sungnyun Kim; Namgyu Ho; Jin-Hwa Kim; Hwanjun Song; Se-Young Yun (CoRR, 2022)

Revisiting the Updates of a Pre-trained Model for Few-shot Learning. - Yujin Kim; Jaehoon Oh; Sungnyun Kim; Se-Young Yun (CoRR, 2022)

Demystifying the Base and Novel Performances for Few-shot Class-incremental Learning. - Jaehoon Oh; Se-Young Yun (CoRR, 2022)

CloudNet: A LiDAR-Based Face Anti-Spoofing Model That Is Robust Against Light Variation. - Yongrae Kim; Hyunmin Gwak; Jaehoon Oh; Minho Kang; Jinkyu Kim 001; Hyun Kwon; Sunghwan Kim 003 (IEEE Access, 2023)

FedSoL: Bridging Global Alignment and Local Generality in Federated Learning. - Gihun Lee; Minchan Jeong; Sangmook Kim; Jaehoon Oh; Se-Young Yun (CoRR, 2023)

Cross-Modal Retrieval Meets Inference: Improving Zero-Shot Classification with Cross-Modal Retrieval. - Seongha Eom; Namgyu Ho; Jaehoon Oh; Se-Young Yun (CoRR, 2023)

FedFN: Feature Normalization for Alleviating Data Heterogeneity Problem in Federated Learning. - Seongyoon Kim; Gihun Lee; Jaehoon Oh; Se-Young Yun (CoRR, 2023)

Effect of Contrast Level and Image Format on a Deep Learning Algorithm for the Detection of Pneumothorax with Chest Radiography. - Myeong Seong Yoon; Gitaek Kwon; Jaehoon Oh; Jongbin Ryu; Jongwoo Lim; Bokyeong Kang; Juncheol Lee; Dongkyoon Han (J. Digit. Imaging, 2023)

FedSOL: Stabilized Orthogonal Learning with Proximal Restrictions in Federated Learning. - Gihun Lee; Minchan Jeong; Sangmook Kim; Jaehoon Oh; Se-Young Yun (CVPR, 2024)

BAPO: Base-Anchored Preference Optimization for Overcoming Forgetting in Large Language Models Personalization. - Gihun Lee; Minchan Jeong; Yujin Kim; Hojung Jung; Jaehoon Oh; SangMook Kim; Se-Young Yun (EMNLP (Findings), 2024)

BAPO: Base-Anchored Preference Optimization for Personalized Alignment in Large Language Models. - Gihun Lee; Minchan Jeong; Yujin Kim; Hojung Jung; Jaehoon Oh; Sangmook Kim; Se-Young Yun (CoRR, 2024)

House of Cards: Massive Weights in LLMs. - Jaehoon Oh; Seungjun Shin; Dokwan Oh (CoRR, 2024)

OrthoRank: Token Selection via Sink Token Orthogonality for Efficient LLM inference. - Seungjun Shin; Jaehoon Oh; Dokwan Oh (CoRR, 2025)