翻译NLP:自然语言处理研究的新范式和一般原则。

Denis Newman-Griffis, Jill Fain Lehman, Carolyn Rosé, Harry Hochheiser
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引用次数: 0

摘要

自然语言处理(NLP)研究通过基础科学将对普遍原理的研究与针对特定用例和设置的应用科学相结合。然而,基础NLP和应用之间的交流过程通常被认为是自然出现的,导致许多创新没有得到应用,许多重要问题没有得到研究。我们描述了一个翻译型NLP的新范式,其目的是构建和促进基础和应用NLP研究相互告知的过程。因此,翻译NLP提出了第三种研究范式,重点是理解应用需求带来的挑战,以及这些挑战如何推动基础科学和技术设计的创新。我们表明,NLP研究的许多重大进展都是从基本原则与应用需求的交叉中出现的,并提出了一个概念框架,概述了转化研究中的利益相关者和关键问题。我们的框架为将翻译型自然语言处理发展为一个专门的研究领域提供了路线图,并确定了一般的翻译原则,以促进基础研究和应用研究之间的交流。
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Translational NLP: A New Paradigm and General Principles for Natural Language Processing Research.

Natural language processing (NLP) research combines the study of universal principles, through basic science, with applied science targeting specific use cases and settings. However, the process of exchange between basic NLP and applications is often assumed to emerge naturally, resulting in many innovations going unapplied and many important questions left unstudied. We describe a new paradigm of Translational NLP, which aims to structure and facilitate the processes by which basic and applied NLP research inform one another. Translational NLP thus presents a third research paradigm, focused on understanding the challenges posed by application needs and how these challenges can drive innovation in basic science and technology design. We show that many significant advances in NLP research have emerged from the intersection of basic principles with application needs, and present a conceptual framework outlining the stakeholders and key questions in translational research. Our framework provides a roadmap for developing Translational NLP as a dedicated research area, and identifies general translational principles to facilitate exchange between basic and applied research.

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