FEWER: Federated Weight Recovery. - Yongjin Shin; Gihun Lee; Seungjae Shin; Seyoung Yun; Il-Chul Moon (DistributedML@CoNEXT, 2020)

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

MixCo: Mix-up Contrastive Learning for Visual Representation. - Sungnyun Kim; Gihun Lee; Sangmin Bae; Se-Young Yun (CoRR, 2020)

Preservation of the Global Knowledge by Not-True Self Knowledge Distillation in Federated Learning. - Gihun Lee; Yongjin Shin; Minchan Jeong; Se-Young Yun (CoRR, 2021)

Self-Contrastive Learning. - Sangmin Bae; Sungnyun Kim; Jongwoo Ko; Gihun Lee; Seungjong Noh; Se-Young Yun (CoRR, 2021)

Deepfake Detection Using the Rate of Change between Frames Based on Computer Vision. - Gihun Lee; Mihui Kim (Sensors, 2021)

Preservation of the Global Knowledge by Not-True Distillation in Federated Learning. - Gihun Lee; Minchan Jeong; Yongjin Shin; Sangmin Bae; Se-Young Yun (NeurIPS, 2022)

MEDIAR: Harmony of Data-Centric and Model-Centric for Multi-Modality Microscopy. - Gihun Lee; SangMook Kim; Joonkee Kim; Se-Young Yun (Cell Segmentation Challenge @ NeurIPS, 2022)

Self-Contrastive Learning: Single-Viewed Supervised Contrastive Framework Using Sub-network. - Sangmin Bae; Sungnyun Kim; Jongwoo Ko; Gihun Lee; Seungjong Noh; Se-Young Yun (AAAI, 2023)

The Multi-modality Cell Segmentation Challenge: Towards Universal Solutions. - Jun Ma 016; Ronald Xie; Shamini Ayyadhury; Cheng Ge; Anubha Gupta; Ritu Gupta; Song Gu; Yao Zhang 010; Gihun Lee; Joonkee Kim; Wei Lou; Haofeng Li; et al. (CoRR, 2023)

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

Distort, Distract, Decode: Instruction-Tuned Model Can Refine its Response from Noisy Instructions. - Taehyeon Kim 001; Joonkee Kim; Gihun Lee; 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)

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)

CUPID: A Real-Time Session-Based Reciprocal Recommendation System for a One-on-One Social Discovery Platform. - Beomsu Kim; Sangbum Kim; Minchan Kim; Joonyoung Yi; Sungjoo Ha; Suhyun Lee; Youngsoo Lee; Gihoon Yeom; Buru Chang; Gihun Lee (ICDM (Workshops), 2024)

Instructive Decoding: Instruction-Tuned Large Language Models are Self-Refiner from Noisy Instructions. - Taehyeon Kim 001; Joonkee Kim; Gihun Lee; Se-Young Yun (ICLR, 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)

Learning to Summarize from LLM-generated Feedback. - Hwanjun Song; Taewon Yun; Yuho Lee; Gihun Lee; Jason Cai; Hang Su (CoRR, 2024)

CUPID: A Real-Time Session-Based Reciprocal Recommendation System for a One-on-One Social Discovery Platform. - Beomsu Kim; Sangbum Kim; Minchan Kim; Joonyoung Yi; Sungjoo Ha; Suhyun Lee; Youngsoo Lee; Gihun Yeom; Buru Chang; Gihun Lee (CoRR, 2024)

Learning to Summarize from LLM-generated Feedback. - Hwanjun Song; Taewon Yun; Yuho Lee; Jihwan Oh; Gihun Lee; Jason Cai; Hang Su (NAACL (Long Papers), 2025)