Dataset Distillation

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4 papers in the last four weeks, with none the four weeks before. 0.0% of all new papers.

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MGPO: Manifold-Guided Diffusion Alignment for Task-Aware Dataset Distillation
Oct 4, 2026Yunyi Chen, Chenru Wang, Xinyi Ye +2Diffusion Model Alignment Dataset Distillation
AGI Lab, Westlake University · Eindhoven University of Technology · Guangdong University of Finance and Economics
Nonparametric Distribution Matching for Self-Supervised Whole-Slide Image Condensation
Sep 30, 2026Duong M. Nguyen, Trong Nghia Hoang, Hang Thi Nguyen +3Computational Pathology Distribution Matching
University of Illinois Urbana-Champaign · Washington State University · Hanoi Medical University +2
The Composition Gap in Dataset Distillation
Sep 28, 2026Guang Li, Takahiro Ogawa, Miki HaseyamaDataset Distillation
Hokkaido University
PSM: Dataset Distillation Based on Precise Statistical Matching by Difficulty
Sep 28, 2026Hongxu Ma, Guang Li, Shijie Wang +6Distribution Matching Dataset Distillation
Zhejiang University · Hokkaido University · The University of Queensland +3
Efficient Video Dataset Distillation via Cluster-Guided Prototype Blending
Aug 4, 2026Chongle Ren, Guang Li, Wenbo Huang +3Dataset Distillation
1Hokkaido University · 2Southeast University
Self-Supervised Representation-Guided Generative Dataset Distillation
Aug 4, 2026Mingzhuo Li, Guang Li, Linfeng Ye +4Diffusion Model Guidance Dataset Distillation
Hokkaido University, Japan · University of Toronto, Canada · University of Tokyo, Japan
Long-Tailed 3D Point Cloud Dataset Distillation
Jul 29, 2026Jiahao You, Xu Han, Jinfeng Xu +1Long-Tailed Classification Dataset Distillation
Huazhong University of Science and Technology · Hunan University
Dataset Distillation Based on Saliency-Driven Prototype Alignment
Jul 28, 2026Yawen Zou, Wenqi Cai, Guang Li +3Prototype Learning Dataset Distillation
University of Toyama · Hokkaido University · University of Fukui
Making Single-Cell Data Distillation Auditable: Traceable Real-Cell Coresets via Discrete Min--Max Selection
Jul 20, 2026Yaodi Luo, Peize He, Lingbei Meng +4Dataset Distillation Coreset Selection
The Chinese University of Hong Kong, Shenzhen · Shenzhen Loop Area Institute, Shenzhen · Shenzhen Research Institute of Big Data, Shenzhen, China
Dataset Distillation by Influence Matching
Jul 18, 2026Haoru Tan, Wang Wang, Sitong Wu +5Dataset Distillation Influence Functions
1HKU · 2CUHK · 3Stanford
Context-Constrained Transfer Learning for Tabular Foundation Models via Data Distillation
Jul 6, 2026Yijun Lin, Sai LiTabular Foundation Models Dataset Distillation
Renmin University of China · Tsinghua University
Condensing Large-Scale Datasets Directly with Minimal Information Loss
Jul 1, 2026Xinyi Shang, Peng Sun, Bei Shi +2Distribution Shift Distribution Matching
University College London, United Kingdom · Zhejiang University, China · Westlake University, China +1
Robust Trajectory Distillation: Hybrid Reweighting Meets Teacher-Inspired Targets
Jun 29, 2026Kaifeng Chen, Lechao Cheng, Jiyang Li +6Dataset Distillation Learning with Noisy Labels
Hefei University of Technology · Jianghuai Advance Technology Center · Anhui Provincial Key Laboratory of Humanoid Robots +2
Rank-Aware Hyperbolic Alignment for Vision-Language Dataset Distillation
Jun 28, 2026Jongoh Jeong, Sun-Kyung Lee, Kuk-Jin YoonDataset Distillation Vision-Language Alignment
Korea Advanced Institute of Science and Technology (KAIST), Republic of Korea · Electronics and Telecommunications Research Institute (ETRI), Republic of Korea
TaLK: Text-attributed Graph Dataset Distillation via Coupling Language Model with Graph-Aware Kernel
Jun 22, 2026Yeongho Kim, Yeonje Choi, Kijung ShinText-Attributed Graph Learning Dataset Distillation
Kim Jaechul Graduate School of AI, KAIST
Structural Assessment for Understanding and Guiding Dataset Distillation in Discrete Token Space
Jun 19, 2026Yue Cao, Jianyang Gu, Vyacheslav Kungurtsev +4Data Selection Dataset Distillation
The University of British Columbia · The Ohio State University · Czech Technical University in Prague +1
Rethinking Dataset Distillation for Classification: Do Distilled Sets Outperform Coresets?
Jun 16, 2026Trisha Mittal, Akshay Mehra, Joshua KimballTraining Data Selection Dataset Distillation
1Dolby Laboratory
TAKE: Trajectory-Aware Knowledge Estimation for Text Dataset Distillation
Jun 13, 2026Tri-Nhan Vo, Dang Nguyen, Sunil GuptaDataset Distillation
Deakin Applied AI Initiative, Deakin University, Australia
Geometry-Aware Dataset Condensation for Diffusion Model Training
Jun 4, 2026Xiao Cui, Yulei Qin, Mo Zhu +3Dataset Distillation Dataset Condensation
University of Science and Technology of China · Independent Researcher · Zhejiang University +1
Pool-Select-Refine for Allocation-Aware Generative Dataset Distillation
Jun 1, 2026Wenmin Li, Shunsuke Sakai, Zhongkai Zhao +1Dataset Distillation Knowledge Distillation
Graduate School of Engineering, University of Fukui, 3-9-1 Bunkyo, Fukui, 910-8507, Fukui, Japan · College of Computer Science and Artificial Intelligence, Southwest Minzu University, No.168, Wenxing Section, Dajian Road, Konggang Development Zone, Shuangliu District, Chengdu, 610225, Sichuan, China
D3S2: Diffusion-Guided Dataset Distillation for Semantic Segmentation
May 24, 2026Wenjie Zheng, Haoji Hu, Jiali Lu +2Diffusion Model Guidance Dataset Distillation
Zhejiang University, China
Multimodal Distribution Matching for Vision-Language Dataset Distillation
May 22, 2026Jongoh Jeong, Hoyong Kwon, Minseok Kim +1Cross-Modal Learning Cross-Modal Alignment
Visual Intelligence Lab., KAIST
Mind Your Margin and Boundary: Are Your Distilled Datasets Truly Robust?
May 20, 2026Muquan Li, Yingyi Ma, Yihong Huang +5Neural Network Robustness Adversarial Robustness
The Laboratory of Intelligent Collaborative Computing of UESTC, Chengdu, China · Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Shenzhen, China · Monash University, Melbourne, Australia
SAS: Semantic-aware Sampling for Generative Dataset Distillation
May 18, 2026Mingzhuo Li, Guang Li, Linfeng Ye +4Training Data Selection Dataset Distillation
Hokkaido University, N-14, W-9, Kita-Ku, Sapporo, 060-0814, Japan · University of Toronto, 27 King’s College Circle, Toronto, Ontario M5S 1A1, Canada · The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8654, Japan
Spectral Gradient Surgery for Domain-Generalizable Dataset Distillation
May 13, 2026Minyoung Oh, Najeong Chae, Jae-Young SimOOD Generalization Distribution Matching
Graduate School of Artificial Intelligence Ulsan National Institute of Science and Technology (UNIST) Ulsan, Republic of Korea
DIVER: Diving Deeper into Distilled Data via Expressive Semantic Recovery
May 12, 2026Qianxin Xia, Zhiyong Shu, Wenbo Jiang +3Dataset Distillation
University of Electronic Science and Technology of China, Chengdu, China · Institute of High Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR), Singapore · Centre for Frontier AI Research (CFAR), Agency for Science, Technology and Research (A*STAR), Singapore.
Closed-Form Linear-Probe Dataset Distillation for Pre-trained Vision Models
May 8, 2026Bincheng Peng, Guang Li, Ping Liu +2Linear Probing Dataset Distillation
Hokkaido University · University of Nevada, Reno
Model-to-Data Distillation for Graph Neural Networks
May 7, 2026Debolina Halder Lina, Arlei SilvaGraph Structure Learning Graph Neural Networks
Department of Computer Science, Rice University, Houston, TX 77005, USA · Department of Computer Science & Ken Kennedy Institute, Rice University, Houston, TX 77005, USA
DMGD: Train-Free Dataset Distillation with Semantic-Distribution Matching in Diffusion Models
May 5, 2026Qichao Wang, Yunhong Lu, Hengyuan Cao +2Diffusion Model Guidance Dataset Distillation
Zhejiang University · Shanghai Institute for Advanced Study-Zhejiang University · Shanghai Institute for Mathematics and Interdisciplinary Sciences
Federated Distillation for Whole Slide Image via Gaussian-Mixture Feature Alignment and Curriculum Integration
May 1, 2026Luru Jing, Cong Cong, Yanyuan Chen +1Computational Pathology Dataset Distillation
School of Computer Science, Peking University, Beijing, China · Center for Health Informatics, Australian Institute of Health Innovation, Macquarie University, Sydney, NSW 2113, Australia · School of Data Science, University of Virginia, Charlottesville, VA, USA.

Oct 4, 2026, cs.CVJ/K move · Enter open · S save

MGPO: Manifold-Guided Diffusion Alignment for Task-Aware Dataset Distillation

Yunyi Chen, Chenru Wang, Xinyi Ye, Zexin Zheng+1

AGI Lab, Westlake University · Eindhoven University of Technology · Guangdong University of Finance and Economics

Diffusion Model Alignment Dataset Distillation RL for Diffusion Models

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Diffusion-based dataset distillation (DD) suffers from a fundamental objective mismatch: likelihood-driven diffusion models prioritize density approximation over the discriminative decision boundaries required for downstream tasks. Beyond semantic mismatch, relying solely on density also leads to geometric coverage loss, where generated samples collapse into a few high-density modes and fail to cover the manifold's structural diversity. We propose Manifold-Guided Policy Optimization (MGPO), which reformulates DD as a multi-objective reinforcement learning problem and achieves Dual-Space Alignment via a pixel-space discriminative reward and a latent-space geometric reward guided by a class-wise Minimum Spanning Tree (MST). The discriminative reward enforces class separability, while the MST-based geometric reward encourages generated latents to cover a sparse geometric skeleton of each class, jointly addressing both failure modes. We further provide an idealized analysis that motivates the MST-based reward, including a Hausdorff approximation bound and a subsampling bound independent of the dataset size. The reward-modular design extends to structured tasks such as object detection and segmentation by substituting the frozen task reward model. Extensive experiments show MGPO consistently outperforms existing methods, including a +8.0% mIoU gain on segmentation under low-budget settings.

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