1 Introduction

2 Taxonomy  
2.1 Basics of Dataset Distillation  
2.2 Taxonomy Explanation

3 Learning Frameworks  
3.1 Meta-Learning  
3.2 Surrogate Objective

4 Common Enhancement Methods  
4.1 Parameterization  
4.2 Augmentation  
4.3 Label Distillation

5 Data Modalities  
5.1 Image  
5.2 Audio  
5.3 Text  
5.4 Graph

6 Applications  
6.1 Computationally Intensive Tasks  
6.2 Privacy  
6.3 Robustness

7 Conclusion and Future Directions  
7.1 Computational Efficiency  
7.2 Performance Degradation on Larger IPC  
7.3 Weak Labels