Task-based dialogue policy learning based on diffusion models
Author:
Funder
National Natural Science Foundation of China
Natural Science Foundation of Shandong Province
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s10489-024-05810-6.pdf
Reference54 articles.
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2. Kwan W, Wang H, Wang H, Wong K (2023) A survey on recent advances and challenges in reinforcement learning methods for task-oriented dialogue policy learning. Int J Autom Comput 20(3):318–334. https://doi.org/10.1007/s11633-022-1347-y
3. Dhingra B, Li L, Li X, Gao J, Chen Y, Ahmed F, Deng L (2017) Towards end-to-end reinforcement learning of dialogue agents for information access. 484–495. https://doi.org/10.18653/v1/P17-1045
4. Shi W, Yu Z (2018) Sentiment adaptive end-to-end dialog systems. 1509–1519. https://doi.org/10.18653/v1/P18-1140
5. Casanueva I, Temcinas T, Gerz D, Henderson M, Vulic I (2020) Efficient intent detection with dual sentence encoders. arXiv:2003.04807
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