PLATO-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
摘要：
为了构建一个高质量的开放域聊天机器人，我们介绍了通过课程学习的PLATO-2的有效培训过程。在学习过程中有两个阶段。在第一阶段中，粗粒度生成模型被训练以在一对一映射的简化框架下学习响应生成。在第二阶段中，进一步训练用潜变量增强的细粒度生成模型和评估模型，以分别生成不同的响应和选择最佳响应。PLATO-2在中文和英文数据上进行了训练，通过综合评估验证了其有效性和优越性，取得了新的最先进的结果。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
