Abstract
To build a high-quality open-domain chatbot, we introduce the effective training process of PLATO-2 via curriculum learning. There are two stages involved in the learning process. In the first stage, a coarse-grained generation model is trained to learn response generation under the simplified framework of one-to-one mapping. In the second stage, a fine-grained generative model augmented with latent variables and an evaluation model are further trained to generate diverse responses and to select the best response, respectively. PLATO-2 was trained on both Chinese and English data, whose effectiveness and superiority are verified through comprehensive evaluations, achieving new state-of-the-art results.
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CITATION STYLE
Bao, S., He, H., Wang, F., Wu, H., Wang, H., Wu, W., … Xu, X. (2021). PLATO-2: Towards Building an Open-Domain Chatbot via Curriculum Learning. In Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021 (pp. 2513–2525). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2021.findings-acl.222
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