Adaptor: A Real-time Module for a Conversational Agent to Adapt Policy Based on Negative User Behavior-Reference-Cited by-同舟云学术

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Adaptor: A Real-time Module for a Conversational Agent to Adapt Policy Based on Negative User Behavior

Published:2021-09-21 Issue: Volume: Page:
ISSN:
Container-title:Adjunct Proceedings of the 2021 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2021 ACM International Symposium on Wearable Computers
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Author:

Shi Chen¹,Zhang Zengming¹,Jiang Feijun¹,Hu Yuxiang¹

Affiliation:

1. Alibaba Group, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3460418.3479274

Reference5 articles.

1. A Scalable Neural Shortlisting-Reranking Approach for Large-Scale Domain Classification in Natural Language Understanding

2. Y Kim D Kim A Kumar and R Sarikaya. 2018. Efficient large-scale neural domain classification with personalized attention. In ACL. ACL Australia 2214–2224. Y Kim D Kim A Kumar and R Sarikaya. 2018. Efficient large-scale neural domain classification with personalized attention. In ACL. ACL Australia 2214–2224.

3. D Park H Yuan D Kim 2020. Large-scale Hybrid Approach for Predicting User Satisfaction with Conversational Agents. preprint arXiv:2006.07113 . (2020) . D Park H Yuan D Kim 2020. Large-scale Hybrid Approach for Predicting User Satisfaction with Conversational Agents. preprint arXiv:2006.07113 . (2020) .

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