In this paper we propose and investigate a novel end-to-end method for automatically generating short email responses, called Smart Reply. It generates semantically diverse suggestions that can be used as complete email responses with just one tap on mobile. The system is currently used in Inbox by Gmail and is responsible for assisting with 10% of all mobile responses. It is designed to work at very high throughput and process hundreds of millions of messages daily. The system exploits state-of-the-art, large-scale deep learning. We describe the architecture of the system as well as the challenges that we faced while building it, like response diversity and scalability. We also introduce a new method for semantic clustering of user-generated content that requires only a modest amount of explicitly labeled data.

本文提出并研究了一种新的端到端方法以自动生成短电子邮件回复，称为“Smart Reply”。它利用先进的大型深度学习生成语义多元化的建议来作为电子邮件的完整响应，并在Inbox邮箱中使用，协助10％的所有移动响应。该系统具有处理每天数亿条消息的能力，利用了最先进的大规模深度学习技术，同时解决了响应多样性和可扩展性等问题，并引入了一种仅需要少量明确标记的数据进行语义聚类的新方法。

智能回复: 电子邮件自动回复建议