1 INTRODUCTION  
1.1 Real-world Examples  
1.2 Motivation and Contribution  
1.3 Organization of the Survey  

2 AN OVERVIEW OF EXTREME MULTI-LABEL LEARNING  
2.1 Problem Definition of XML  
2.2 Comparison with Other Settings  
2.3 The Challenges of XML  

3 TAXONOMY OF XML  
3.1 Model Architecture  
3.2 The Long-Tailed Label Distribution  
3.3 Weakly Supervised XML  

4 RUN EXPERIMENTS IN XML  
4.1 Implementations  
4.2 Commonly Used Benchmark Datasets  
4.3 Evaluation Metrics  

5 FUTURE RESEARCH DIRECTIONS  
5.1 Problems of Existing Methodologies  
5.2 The Tail Label Problem  
5.3 Weakly Supervised XML  
5.4 Modeling Label Correlations  
5.5 XML Meets Computer Vision  

6 CONCLUSION