A Survey on Recent Advances in LLM-Based Multi-turn Dialogue Systems
Zihao Yi Jiarui Ouyang Yuwen Liu Tianhao Liao Zhe Xu Ying Shen
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.