  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.
