Se-Young Yun

papers

557

total citations

papers (15)

Preservation of the Global Knowledge by Not-True Distillation in Federated Learning

NEURIPS 2022arXiv

183

citations

FINE Samples for Learning with Noisy Labels

NEURIPS 2021arXiv

123

citations

DistiLLM: Towards Streamlined Distillation for Large Language Models

ICML 2024arXiv

citations

Understanding Cross-Domain Few-Shot Learning Based on Domain Similarity and Few-Shot Difficulty

NEURIPS 2022arXiv

citations

PLASTIC: Improving Input and Label Plasticity for Sample Efficient Reinforcement Learning

NEURIPS 2023arXiv

citations

Re-Thinking Federated Active Learning Based on Inter-Class Diversity

CVPR 2023arXiv

citations

FedSOL: Stabilized Orthogonal Learning with Proximal Restrictions in Federated Learning

CVPR 2024arXiv

citations

Coreset Sampling From Open-Set for Fine-Grained Self-Supervised Learning

CVPR 2023arXiv

citations

Fair Streaming Principal Component Analysis: Statistical and Algorithmic Viewpoint

NEURIPS 2023arXiv

citations

Leveraging Normalization Layer in Adapters with Progressive Learning and Adaptive Distillation for Cross-Domain Few-Shot Learning

AAAI 2024arXiv

citations

Synergistic Integration of Coordinate Network and Tensorial Feature for Improving Neural Radiance Fields from Sparse Inputs

ICML 2024arXiv

citations

MAVFlow: Preserving Paralinguistic Elements with Conditional Flow Matching for Zero-Shot AV2AV Multilingual Translation

ICCV 2025arXiv

citations

Se-Young Yun

papers (15)

Preservation of the Global Knowledge by Not-True Distillation in Federated Learning

FINE Samples for Learning with Noisy Labels

DistiLLM: Towards Streamlined Distillation for Large Language Models

Understanding Cross-Domain Few-Shot Learning Based on Domain Similarity and Few-Shot Difficulty

PLASTIC: Improving Input and Label Plasticity for Sample Efficient Reinforcement Learning

Re-Thinking Federated Active Learning Based on Inter-Class Diversity

FedSOL: Stabilized Orthogonal Learning with Proximal Restrictions in Federated Learning

Coreset Sampling From Open-Set for Fine-Grained Self-Supervised Learning

Fair Streaming Principal Component Analysis: Statistical and Algorithmic Viewpoint

Leveraging Normalization Layer in Adapters with Progressive Learning and Adaptive Distillation for Cross-Domain Few-Shot Learning

KLASS: KL-Guided Fast Inference in Masked Diffusion Models

Regret in Online Recommendation Systems

Robust Streaming PCA

Synergistic Integration of Coordinate Network and Tensorial Feature for Improving Neural Radiance Fields from Sparse Inputs

MAVFlow: Preserving Paralinguistic Elements with Conditional Flow Matching for Zero-Shot AV2AV Multilingual Translation

papers (15)

Preservation of the Global Knowledge by Not-True Distillation in Federated Learning

FINE Samples for Learning with Noisy Labels

DistiLLM: Towards Streamlined Distillation for Large Language Models

Understanding Cross-Domain Few-Shot Learning Based on Domain Similarity and Few-Shot Difficulty

PLASTIC: Improving Input and Label Plasticity for Sample Efficient Reinforcement Learning

Re-Thinking Federated Active Learning Based on Inter-Class Diversity

FedSOL: Stabilized Orthogonal Learning with Proximal Restrictions in Federated Learning

Coreset Sampling From Open-Set for Fine-Grained Self-Supervised Learning

Fair Streaming Principal Component Analysis: Statistical and Algorithmic Viewpoint

Leveraging Normalization Layer in Adapters with Progressive Learning and Adaptive Distillation for Cross-Domain Few-Shot Learning

KLASS: KL-Guided Fast Inference in Masked Diffusion Models

Regret in Online Recommendation Systems

Robust Streaming PCA

Synergistic Integration of Coordinate Network and Tensorial Feature for Improving Neural Radiance Fields from Sparse Inputs

MAVFlow: Preserving Paralinguistic Elements with Conditional Flow Matching for Zero-Shot AV2AV Multilingual Translation