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Sangwoo Mo
标题
引用次数
引用次数
年份
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
5842020
Freeze the Discriminator: a Simple Baseline for Fine-Tuning GANs
S Mo, M Cho, J Shin
CVPR AI for Content Creation Workshop, 2020
2302020
InstaGAN: Instance-aware Image-to-Image Translation
S Mo, M Cho, J Shin
International Conference on Learning Representations, 2019
2052019
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
1782022
Layer-adaptive sparsity for the Magnitude-based Pruning
J Lee, S Park, S Mo, S Ahn, J Shin
International Conference on Learning Representations, 2021
1342021
Lookahead: A Far-Sighted Alternative of Magnitude-based Pruning
S Park*, J Lee*, S Mo, J Shin
International Conference on Learning Representations, 2020
992020
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
522021
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
402021
MASKER: Masked Keyword Regularization for Reliable Text Classification
SJ Moon*, S Mo*, K Lee, J Lee, J Shin
AAAI Conference on Artificial Intelligence, 2021
332021
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
262019
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
192017
Mining GOLD Samples for Conditional GANs
S Mo, C Kim, S Kim, M Cho, J Shin
Advances in Neural Information Processing Systems, 2019
152019
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
82021
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
62023
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
52024
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
52023
OAMixer: Object-aware Mixing Layer for Vision Transformers
H Kang*, S Mo*, J Shin
CVPR Transformers for Vision Workshop, 2022
5*2022
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