论文标题
柏拉图-2：通过课程学习构建开放域聊天机器人
PLATO-2: Towards Building an Open-Domain Chatbot via Curriculum Learning
论文作者
论文摘要
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的有效培训过程。学习过程中涉及两个阶段。在第一阶段，训练了一个粗粒的生成模型，可以在一对一映射的简化框架下学习响应生成。在第二阶段，通过潜在变量增强的细粒生成模型和评估模型进一步训练以产生多种响应并分别选择最佳响应。 Plato-2接受了中文和英语数据的培训，这些数据的有效性和优势通过全面的评估得到了验证，从而实现了新的最新结果。
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.
