1. INTRODUCTION

2. DEEP MULTI-TASK ARCHITECTURES  
2.1 Historical Overview and Taxonomy  
2.2 Encoder-focused Architectures  
2.3 Decoder-Focused Architectures  
2.4 Other Approaches  

3. OPTIMIZATION IN MTL  
3.1 Task Balancing Approaches  
3.2 Other Approaches  

4. EXPERIMENTS  
4.1 Experimental Setup  
4.2 Overview  
4.3 Architectures  
4.4 Task Balancing  
4.5 Limitations  

5. RELATED DOMAINS  
5.1 Multi-Domain Learning  
5.2 Transfer Learning  
5.3 Neural Architecture Search  
5.4 Other  

6. CONCLUSION