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 generation model and an evaluation model are further trained to learn diverse response generation and response coherence estimation, 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.

中文翻译：

---

PLATO-2：通过课程学习构建开放域聊天机器人

为了构建高质量的开放域聊天机器人，我们通过课程学习介绍了 PLATO-2 的有效训练过程。学习过程涉及两个阶段。在第一阶段，训练一个粗粒度的生成模型，在一对一映射的简化框架下学习响应生成。在第二阶段，进一步训练细粒度生成模型和评估模型，分别学习不同的响应生成和响应一致性估计。PLATO-2采用中英文数据进行训练，通过综合评估验证其有效性和优越性，取得了最新的最新成果。