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Dataset Distillation

Dataset distillation is the task of synthesizing a small dataset such that models trained on it achieve high performance on the original large dataset. A dataset distillation algorithm takes as input a large real dataset to be distilled (training set), and outputs a small synthetic distilled dataset, which is evaluated via testing models trained on this distilled dataset on a separate real dataset (validation/test set). A good small distilled dataset is not only useful in dataset understanding, but has various applications (e.g., continual learning, privacy, neural architecture search, etc.).

Papers

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Showing 1–50 of 216 papers

TitleStatusHype
Information-Guided Diffusion Sampling for Dataset Distillation—0
Task-Specific Generative Dataset Distillation with Difficulty-Guided Sampling—0
Dataset Distillation via Vision-Language Category PrototypeCode1
FADRM: Fast and Accurate Data Residual Matching for Dataset DistillationCode1
CaO_2: Rectifying Inconsistencies in Diffusion-Based Dataset DistillationCode1
FedWSIDD: Federated Whole Slide Image Classification via Dataset Distillation—0
Dataset distillation for memorized data: Soft labels can leak held-out teacher knowledgeCode0
Flowing Datasets with Wasserstein over Wasserstein Gradient FlowsCode1
OD3: Optimization-free Dataset Distillation for Object DetectionCode1
Hyperbolic Dataset Distillation—0
Data-Distill-Net: A Data Distillation Approach Tailored for Reply-based Continual Learning—0
Diversity-Driven Generative Dataset Distillation Based on Diffusion Model with Self-Adaptive Memory—0
MGD^3: Mode-Guided Dataset Distillation using Diffusion Models—0
CONCORD: Concept-Informed Diffusion for Dataset DistillationCode0
Taming Diffusion for Dataset Distillation with High RepresentativenessCode1
Exploring Generalized Gait Recognition: Reducing Redundancy and Noise within Indoor and Outdoor DatasetsCode0
Contrastive Learning-Enhanced Trajectory Matching for Small-Scale Dataset Distillation—0
DD-Ranking: Rethinking the Evaluation of Dataset DistillationCode2
Beyond Modality Collapse: Representations Blending for Multimodal Dataset Distillation—0
Leveraging Multi-Modal Information to Enhance Dataset Distillation—0
Video Dataset Condensation with Diffusion Models—0
Dataset Distillation with Probabilistic Latent Features—0
UniDetox: Universal Detoxification of Large Language Models via Dataset DistillationCode0
Latent Video Dataset Distillation—0
Distribution-aware Dataset Distillation for Efficient Image Restoration—0
Knowledge Distillation and Dataset Distillation of Large Language Models: Emerging Trends, Challenges, and Future Directions—0
Permutation-Invariant and Orientation-Aware Dataset Distillation for 3D Point Clouds—0
Curriculum Coarse-to-Fine Selection for High-IPC Dataset DistillationCode0
Enhancing Dataset Distillation via Non-Critical Region RefinementCode0
Generative Dataset Distillation using Min-Max Diffusion Model—0
Finding Stable Subnetworks at Initialization with Dataset Distillation—0
Dataset Distillation for Quantum Neural Networks—0
Robust Dataset Distillation by Matching Adversarial Trajectories—0
Distilling Dataset into Neural FieldCode1
Understanding Dataset Distillation via Spectral Filtering—0
Secure Federated Data Distillation—0
Does Training with Synthetic Data Truly Protect Privacy?Code0
The Evolution of Dataset Distillation: Toward Scalable and Generalizable Solutions—0
Trust-Aware Diversion for Data-Effective Distillation—0
Dark Distillation: Backdooring Distilled Datasets without Accessing Raw Data—0
TD3: Tucker Decomposition Based Dataset Distillation Method for Sequential RecommendationCode0
Knowledge Hierarchy Guided Biological-Medical Dataset Distillation for Domain LLM Training—0
On Learning Representations for Tabular Data Distillation—0
Class-Imbalanced-Aware Adaptive Dataset Distillation for Scalable Pretrained Model on Credit Scoring—0
Dataset Distillation as Pushforward Optimal Quantization—0
Dataset Distillation via Committee VotingCode1
FocusDD: Real-World Scene Infusion for Robust Dataset Distillation—0
Generative Dataset Distillation Based on Self-knowledge Distillation—0
Towards Universal Dataset Distillation via Task-Driven Diffusion—0
OPTICAL: Leveraging Optimal Transport for Contribution Allocation in Dataset Distillation—0
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