CCS Concepts:  $\cdot$   Computing methodologies  $\rightarrow$  Discourse, dialogue and pragmatics ;  $\cdot$   General and reference  $\rightarrow$  Surveys and overviews .

1 INTRODUCTION
1.1 What is Multi-turn Dialogue System?
1.2 Why a Survey on LLM-based Multi-turn Dialogue System?
1.3 Contribution of this Survey

2 GENERAL METHODS
2.1 Decoder-only Transformer Architecture
2.2 Encoder-only Transformer Architecture
2.3 Encoder-decoder Transformer Architecture

3 FINE-TUNING
3.1 Full Fine-Tuning
3.2 Parameter-efficient Fine-Tuning
3.3 Mitigating Fine-Tuning Instabilities

4 PROMPT ENGINEERING
4.1 Prompt Tuning
4.2 Tuning-free Prompting

5 LLM BASED TASK-ORIENTED DIALOGUE SYSTEMS
5.1 Pipeline-based Methods
5.2 End-to-End Methods

6 LLM BASED OPEN-DOMAIN DIALOGUE SYSTEMS
6.1 Retrieval-based Methods
6.2 Generation-based Methods
6.3 Hybrid Methods

7 EVALUATION APPROACHES
7.1 Automatic Evaluation
7.2 Human Evaluation

8 DATASETS
8.1 Datasets for Task-oriented Dialogue Systems
8.2 Datasets for Open-domain Dialogue Systems

9 DISCUSSION

10 CONCLUSION