Exploring the Impact of Dataset Bias on Dataset Distillation
Fuente:
arXiv
Saved in:
| Main Authors: | Lu, Yao, Gu, Jianyang, Chen, Xuguang, Vahidian, Saeed, Xuan, Qi |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Group Distributionally Robust Dataset Distillation with Risk Minimization
by: Vahidian, Saeed, et al.
Published: (2024)
by: Vahidian, Saeed, et al.
Published: (2024)
Efficient Dataset Distillation via Minimax Diffusion
by: Gu, Jianyang, et al.
Published: (2023)
by: Gu, Jianyang, et al.
Published: (2023)
CONCORD: Concept-Informed Diffusion for Dataset Distillation
by: Gu, Jianyang, et al.
Published: (2025)
by: Gu, Jianyang, et al.
Published: (2025)
Taming Diffusion for Dataset Distillation with High Representativeness
by: Zhao, Lin, et al.
Published: (2025)
by: Zhao, Lin, et al.
Published: (2025)
Mitigating Bias in Dataset Distillation
by: Cui, Justin, et al.
Published: (2024)
by: Cui, Justin, et al.
Published: (2024)
Towards Trustworthy Dataset Distillation
by: Ma, Shijie, et al.
Published: (2023)
by: Ma, Shijie, et al.
Published: (2023)
Temporal Saliency-Guided Distillation: A Scalable Framework for Distilling Video Datasets
by: Gu, Xulin, et al.
Published: (2025)
by: Gu, Xulin, et al.
Published: (2025)
Low-Rank Similarity Mining for Multimodal Dataset Distillation
by: Xu, Yue, et al.
Published: (2024)
by: Xu, Yue, et al.
Published: (2024)
Improve Cross-Architecture Generalization on Dataset Distillation
by: Zhou, Binglin, et al.
Published: (2024)
by: Zhou, Binglin, et al.
Published: (2024)
Dataset Distillers Are Good Label Denoisers In the Wild
by: Cheng, Lechao, et al.
Published: (2024)
by: Cheng, Lechao, et al.
Published: (2024)
Dataset Distillation from First Principles: Integrating Core Information Extraction and Purposeful Learning
by: Kungurtsev, Vyacheslav, et al.
Published: (2024)
by: Kungurtsev, Vyacheslav, et al.
Published: (2024)
Multi-Modal Dataset Distillation in the Wild
by: Dang, Zhuohang, et al.
Published: (2025)
by: Dang, Zhuohang, et al.
Published: (2025)
On the Diversity and Realism of Distilled Dataset: An Efficient Dataset Distillation Paradigm
by: Sun, Peng, et al.
Published: (2023)
by: Sun, Peng, et al.
Published: (2023)
Understanding Bias in Large-Scale Visual Datasets
by: Zeng, Boya, et al.
Published: (2024)
by: Zeng, Boya, et al.
Published: (2024)
Understanding Dataset Distillation via Spectral Filtering
by: Bo, Deyu, et al.
Published: (2025)
by: Bo, Deyu, et al.
Published: (2025)
Dataset Distillation as Data Compression: A Rate-Utility Perspective
by: Bao, Youneng, et al.
Published: (2025)
by: Bao, Youneng, et al.
Published: (2025)
Hyperbolic Dataset Distillation
by: Li, Wenyuan, et al.
Published: (2025)
by: Li, Wenyuan, et al.
Published: (2025)
A Decade's Battle on Dataset Bias: Are We There Yet?
by: Liu, Zhuang, et al.
Published: (2024)
by: Liu, Zhuang, et al.
Published: (2024)
Towards Adversarially Robust Dataset Distillation by Curvature Regularization
by: Xue, Eric, et al.
Published: (2024)
by: Xue, Eric, et al.
Published: (2024)
DataDAM: Efficient Dataset Distillation with Attention Matching
by: Sajedi, Ahmad, et al.
Published: (2023)
by: Sajedi, Ahmad, et al.
Published: (2023)
Spectral Gradient Surgery for Domain-Generalizable Dataset Distillation
by: Oh, Minyoung, et al.
Published: (2026)
by: Oh, Minyoung, et al.
Published: (2026)
Exploring 3D Dataset Pruning
by: Zhao, Xiaohan, et al.
Published: (2026)
by: Zhao, Xiaohan, et al.
Published: (2026)
Modeling Saliency Dataset Bias
by: Kümmerer, Matthias, et al.
Published: (2025)
by: Kümmerer, Matthias, et al.
Published: (2025)
Distilling Dataset into Neural Field
by: Shin, Donghyeok, et al.
Published: (2025)
by: Shin, Donghyeok, et al.
Published: (2025)
A Label is Worth a Thousand Images in Dataset Distillation
by: Qin, Tian, et al.
Published: (2024)
by: Qin, Tian, et al.
Published: (2024)
Rethinking Dataset Distillation: Hard Truths about Soft Labels
by: Dey, Priyam, et al.
Published: (2026)
by: Dey, Priyam, et al.
Published: (2026)
Beyond Modality Collapse: Representations Blending for Multimodal Dataset Distillation
by: Zhang, Xin, et al.
Published: (2025)
by: Zhang, Xin, et al.
Published: (2025)
Beyond Random: Automatic Inner-loop Optimization in Dataset Distillation
by: Li, Muquan, et al.
Published: (2025)
by: Li, Muquan, et al.
Published: (2025)
Evaluating Pre-Training Bias on Severe Acute Respiratory Syndrome Dataset
by: Rodrigues, Diego Dimer
Published: (2024)
by: Rodrigues, Diego Dimer
Published: (2024)
Generative Dataset Distillation Based on Self-knowledge Distillation
by: Li, Longzhen, et al.
Published: (2025)
by: Li, Longzhen, et al.
Published: (2025)
Source Matters: Source Dataset Impact on Model Robustness in Medical Imaging
by: Juodelyte, Dovile, et al.
Published: (2024)
by: Juodelyte, Dovile, et al.
Published: (2024)
FairDD: Fair Dataset Distillation
by: Zhou, Qihang, et al.
Published: (2024)
by: Zhou, Qihang, et al.
Published: (2024)
Unlocking Dataset Distillation with Diffusion Models
by: Moser, Brian B., et al.
Published: (2024)
by: Moser, Brian B., et al.
Published: (2024)
Importance-Aware Adaptive Dataset Distillation
by: Li, Guang, et al.
Published: (2024)
by: Li, Guang, et al.
Published: (2024)
Dataset Distillation as Pushforward Optimal Quantization
by: Tan, Hong Ye, et al.
Published: (2025)
by: Tan, Hong Ye, et al.
Published: (2025)
Dataset Distillation via the Wasserstein Metric
by: Liu, Haoyang, et al.
Published: (2023)
by: Liu, Haoyang, et al.
Published: (2023)
Distill Gold from Massive Ores: Bi-level Data Pruning towards Efficient Dataset Distillation
by: Xu, Yue, et al.
Published: (2023)
by: Xu, Yue, et al.
Published: (2023)
GIFT: Unlocking Full Potential of Labels in Distilled Dataset at Near-zero Cost
by: Shang, Xinyi, et al.
Published: (2024)
by: Shang, Xinyi, et al.
Published: (2024)
Diversity-Driven Synthesis: Enhancing Dataset Distillation through Directed Weight Adjustment
by: Du, Jiawei, et al.
Published: (2024)
by: Du, Jiawei, et al.
Published: (2024)
Generative Dataset Distillation Based on Diffusion Model
by: Su, Duo, et al.
Published: (2024)
by: Su, Duo, et al.
Published: (2024)
Similar Items
-
Group Distributionally Robust Dataset Distillation with Risk Minimization
by: Vahidian, Saeed, et al.
Published: (2024) -
Efficient Dataset Distillation via Minimax Diffusion
by: Gu, Jianyang, et al.
Published: (2023) -
CONCORD: Concept-Informed Diffusion for Dataset Distillation
by: Gu, Jianyang, et al.
Published: (2025) -
Taming Diffusion for Dataset Distillation with High Representativeness
by: Zhao, Lin, et al.
Published: (2025) -
Mitigating Bias in Dataset Distillation
by: Cui, Justin, et al.
Published: (2024)