自然语言生成
Natural Language Generation
AI总结：
本文概述了自然语言生成（NLG）领域，探讨了其定义、与机器翻译和对话系统的关系，并指出大型语言模型的兴起使自然语言处理各子领域在生成与评估方法上趋于一致。
摘要：
本文简要概述了自然语言生成领域。自然语言生成（NLG）这一术语在最广义的定义下，指的是研究通过自然语言将某种形式的信息表达出来的系统。这些信息可以存储在大型数据库或知识图谱中（在数据到文本应用中），但NLG研究人员也可能研究摘要生成（文本到文本）或图像描述生成（图像到文本）等任务。作为自然语言处理的子领域，NLG与机器翻译（MT）和对话系统等其他子学科密切相关。一些NLG研究人员将MT排除在该领域的定义之外，因为MT不涉及系统需要决定说什么的内容选择过程。相反，对话系统通常不被归入自然语言生成的范畴，因为NLG只是对话系统的一个组成部分（其他组成部分为自然语言理解和对话管理）。然而，随着大型语言模型（LLMs）的兴起，自然语言处理的不同子领域在自然语言生成和自动生成文本的评估方面趋于采用相似的方法论。
英文摘要：
This article provides a brief overview of the field of Natural Language Generation. The term Natural Language Generation (NLG), in its broadest definition, refers to the study of systems that verbalize some form of information through natural language. That information could be stored in a large database or knowledge graph (in data-to-text applications), but NLG researchers may also study summarisation (text-to-text) or image captioning (image-to-text), for example. As a subfield of Natural Language Processing, NLG is closely related to other sub-disciplines such as Machine Translation (MT) and Dialog Systems. Some NLG researchers exclude MT from their definition of the field, since there is no content selection involved where the system has to determine what to say. Conversely, dialog systems do not typically fall under the header of Natural Language Generation since NLG is just one component of dialog systems (the others being Natural Language Understanding and Dialog Management). However, with the rise of Large Language Models (LLMs), different subfields of Natural Language Processing have converged on similar methodologies for the production of natural language and the evaluation of automatically generated text.
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。
