Exploiting Activation Sparsity for Fast CNN Inference on Mobile GPUs. - Chanyoung Oh; Junhyuk So; Sumin Kim; Youngmin Yi (ACM Trans. Embed. Comput. Syst., 2021)

Learning Fair Representation via Distributional Contrastive Disentanglement. - Changdae Oh; Heeji Won; Junhyuk So; Taero Kim; Yewon Kim; Hosik Choi; Kyungwoo Song (KDD, 2022)

Multi-Modal Mixup for Robust Fine-tuning. - Junhyuk So; Changdae Oh; Minchul Shin; Kyungwoo Song (CoRR, 2022)

NIPQ: Noise Injection Pseudo Quantization for Automated DNN Optimization. - Sein Park; Junhyuk So; Juncheol Shin; Eunhyeok Park (CoRR, 2022)

NIPQ: Noise proxy-based Integrated Pseudo-Quantization. - Juncheol Shin; Junhyuk So; Sein Park; Seungyeop Kang; Sungjoo Yoo; Eunhyeok Park (CVPR, 2023)

Geodesic Multi-Modal Mixup for Robust Fine-Tuning. - Changdae Oh; Junhyuk So; Hoyoon Byun; YongTaek Lim; Minchul Shin; Jong-June Jeon; Kyungwoo Song (NeurIPS, 2023)

Temporal Dynamic Quantization for Diffusion Models. - Junhyuk So; Jungwon Lee; Daehyun Ahn; Hyungjun Kim; Eunhyeok Park (NeurIPS, 2023)

Robust Contrastive Learning With Dynamic Mixed Margin. - Junhyuk So; YongTaek Lim; Yewon Kim; Changdae Oh; Kyungwoo Song (IEEE Access, 2023)

FRDiff: Feature Reuse for Exquisite Zero-shot Acceleration of Diffusion Models. - Junhyuk So; Jungwon Lee; Eunhyeok Park (CoRR, 2023)

FRDiff : Feature Reuse for Universal Training-Free Acceleration of Diffusion Models. - Junhyuk So; Jungwon Lee; Eunhyeok Park (ECCV (73), 2024)

PCM : Picard Consistency Model for Fast Parallel Sampling of Diffusion Models. - Junhyuk So; Jiwoong Shin; Chaeyeon Jang; Eunhyeok Park (CVPR, 2025)