Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing 2023
DOI: 10.18653/v1/2023.emnlp-main.363
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End-to-end Task-oriented Dialogue: A Survey of Tasks, Methods, and Future Directions

Libo Qin,
Wenbo Pan,
Qiguang Chen
et al.

Abstract: End-to-end task-oriented dialogue (EToD) can directly generate responses in an end-to-end fashion without modular training, which attracts escalating popularity. The advancement of deep neural networks, especially the successful use of large pre-trained models, has further led to significant progress in EToD research in recent years. In this paper, we present a thorough review and provide a unified perspective to summarize existing approaches as well as recent trends to advance the development of EToD research… Show more

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