# A Survey on Recent Advances in LLM-Based Multi-turn Dialogue Systems

**Authors:** Zihao Yi, Jiarui Ouyang, Yuwen Liu, Tianhao Liao, Zhe Xu, Ying Shen  
**arXiv:** [2402.18013](https://arxiv.org/abs/2402.18013)  
**Date:** 2024-02-28  
**Summary page:** https://www.summarizepaper.com/fr/paper/2402.18013v1/

## Abstract

This survey provides a comprehensive review of research on multi-turn dialogue systems, with a particular focus on multi-turn dialogue systems based on large language models (LLMs). This paper aims to (a) give a summary of existing LLMs and approaches for adapting LLMs to downstream tasks; (b) elaborate recent advances in multi-turn dialogue systems, covering both LLM-based open-domain dialogue (ODD) and task-oriented dialogue (TOD) systems, along with datasets and evaluation metrics; (c) discuss some future emphasis and recent research problems arising from the development of LLMs and the increasing demands on multi-turn dialogue systems.