Due to the significance and value in human-computer interaction and natural
language processing, task-oriented dialog systems are attracting more and more
attention in both academic and industrial communities. In this paper, we survey
recent advances and challenges in task-oriented dialog systems. We also discuss
three critical topics for task-oriented dialog systems: (1) improving data
efficiency to facilitate dialog modeling in low-resource settings, (2) modeling
multi-turn dynamics for dialog policy learning to achieve better
task-completion performance, and (3) integrating domain ontology knowledge into
the dialog model. Besides, we review the recent progresses in dialog evaluation
and some widely-used corpora. We believe that this survey, though incomplete,
can shed a light on future research in task-oriented dialog systems.

本文探讨了任务导向对话系统的最新研究进展和挑战，特别在三个关键领域进行了深入讨论：提高数据效率、模拟多回合动态以优化任务完成性能，以及将领域本体知识与对话模型集成。此外，还评估了最近的对话进展和一些常用的语料库。我们相信，这虽然不是一个完整的调查，但它仍然可以为未来任务导向对话系统的研究提供启示。