1 INTRODUCTION  
1.1 Major Differences  
1.2 Main Contributions  
1.3 Organization  
2 BACKGROUND  
2.1 Categorization  
2.2 Problem Formulation  
2.3 Evaluation Metrics  
2.4 Summarization Datasets  
3 SUMMARIZATION METHODS PRIOR TO LLMS  
3.1 Statistical Summarization Methods  
3.2 Deep Learning Summarization Methods  
3.3 Pre-trained Language Model Summarization Methods  
4 LLM-BASED SUMMARIZATION RESEARCH  
4.1 Benchmarking Studies  
4.2 Modeling Studies  
4.3 Evaluation Studies  
5 OPEN PROBLEMS AND FUTURE DIRECTIONS  
5.1 Quantitative Results  
5.2 Research Trends  
5.3 Open Challenges  
5.4 Future Directions  
6 CONCLUSION