1 Introduction  
2 Preliminary  
2.1 Multilingual Models  
2.2 Pre-Trained Language Models  
2.3 Multilingual Paradigm Transition  
3 Large Language Models with Multilingual Capability  
3.1 Training from Scratch  
3.2 Continual Training  
3.3 Limitations and Future Directions on Training Paradigm  
4 Multilingual Inference Strategies  
4.2 Pre-Translation Inference  
4.3 Multilingual CoT  
4.4 Multilingual Retrieval Augmented Generation  
4.5 Code-Switching  
4.6 Limitations and Future Directions on Inference Strategies  
5 Security of Multilingual Large Language Models  
5.1 Attack Methods  
5.2 Defense Methods  
5.3 Limitations and Future Directions on LLM Security  
6 Multi-Domain LLMs in Multilingual Scenarios  
6.1 Medical Domain  
6.2 Legal Domain  
6.3 Limitations and Future Directions on Multi-Domain  
7 Multilingual Data Resource  
8 Multilingual Benchmark and Evaluation  
9 Bias and Fairness  
9.1 Bias Categories  
9.2 Multilingual Debias  
9.3 Limitations and Discussion  
10 Conclusion and Future Directions