| CSI: Novelty Detection via Contrastive Learning on Distributionally Shifted Instances J Tack*, S Mo*, J Jeong, J Shin Advances in Neural Information Processing Systems, 2020 | 584 | 2020 |
| Freeze the Discriminator: a Simple Baseline for Fine-Tuning GANs S Mo, M Cho, J Shin CVPR AI for Content Creation Workshop, 2020 | 230 | 2020 |
| InstaGAN: Instance-aware Image-to-Image Translation S Mo, M Cho, J Shin International Conference on Learning Representations, 2019 | 205 | 2019 |
| Generating Videos with Dynamics-aware Implicit Generative Adversarial Networks S Yu*, J Tack*, S Mo*, H Kim, J Kim, JW Ha, J Shin International Conference on Learning Representations, 2022 | 178 | 2022 |
| Layer-adaptive sparsity for the Magnitude-based Pruning J Lee, S Park, S Mo, S Ahn, J Shin International Conference on Learning Representations, 2021 | 134 | 2021 |
| Lookahead: A Far-Sighted Alternative of Magnitude-based Pruning S Park*, J Lee*, S Mo, J Shin International Conference on Learning Representations, 2020 | 99 | 2020 |
| Deep neural network based electrical impedance tomographic sensing methodology for large-area robotic tactile sensing H Park, K Park, S Mo, J Kim IEEE Transactions on Robotics 37 (5), 1570-1583, 2021 | 52 | 2021 |
| Object-aware Contrastive Learning for Debiased Scene Representation S Mo*, H Kang*, K Sohn, CL Li, J Shin Advances in Neural Information Processing Systems, 2021 | 40 | 2021 |
| MASKER: Masked Keyword Regularization for Reliable Text Classification SJ Moon*, S Mo*, K Lee, J Lee, J Shin AAAI Conference on Artificial Intelligence, 2021 | 33 | 2021 |
| Deep Neural Network Approach in Electrical Impedance Tomography-based Real-time Soft Tactile Sensor H Park, H Lee, K Park, S Mo, J Kim 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2019 | 26 | 2019 |
| Discovering and Mitigating Visual Biases through Keyword Explanation Y Kim, S Mo, M Kim, K Lee, J Lee, J Shin Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 22* | 2024 |
| Contextual multi-armed bandits under feature uncertainty S Yun, JH Nam, S Mo, J Shin Los Alamos National Lab.(LANL), Los Alamos, NM (United States), 2017 | 19 | 2017 |
| Mining GOLD Samples for Conditional GANs S Mo, C Kim, S Kim, M Cho, J Shin Advances in Neural Information Processing Systems, 2019 | 15 | 2019 |
| SuRe: Improving Open-domain Question Answering of LLMs via Summarized Retrieval J Kim, J Nam, S Mo, J Park, SW Lee, M Seo, JW Ha, J Shin International Conference on Learning Representations, 2023 | 11* | 2023 |
| Abstract Reasoning via Logic-guided Generation S Yu, S Mo, S Ahn, J Shin ICML Self-Supervised Learning for Reasoning and Perception Workshop, 2021 | 8 | 2021 |
| S-CLIP: Semi-supervised Vision-Language Learning using Few Specialist Captions S Mo, M Kim, K Lee, J Shin Advances in Neural Information Processing Systems, 2023 | 7* | 2023 |
| RoPAWS: Robust Semi-supervised Representation Learning from Uncurated Data S Mo, JC Su, CY Ma, M Assran, I Misra, L Yu, S Bell International Conference on Learning Representations, 2023 | 6 | 2023 |
| Hierarchical Context Merging: Better Long Context Understanding for Pre-trained LLMs W Song*, S Oh*, S Mo, J Kim, S Yun, JW Ha, J Shin International Conference on Learning Representations, 2024 | 5 | 2024 |
| Breaking the Spurious Causality of Conditional Generation via Fairness Intervention with Corrective Sampling J Nam, S Mo, J Lee, J Shin Transactions on Machine Learning Research, 2023 | 5 | 2023 |
| OAMixer: Object-aware Mixing Layer for Vision Transformers H Kang*, S Mo*, J Shin CVPR Transformers for Vision Workshop, 2022 | 5* | 2022 |
Jinwoo ShinKAIST Endowed Chair Professor在 kaist.ac.kr 的电子邮件经过验证
