Harnessing Knowledge and Reasoning for Human-Like Natural Language Generation: A Brief Review
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Abstract (arXiv)
The rapid development and application of natural language generation (NLG) techniques has revolutionized the field of automatic text production. However, these techniques are still limited in their ability to produce human-like text that is truly reasonable and informative. In this paper, we explore the importance of NLG being guided by knowledge, in order to convey human-like reasoning through language generation. We propose ten goals for intelligent NLG systems to pursue, and briefly review the achievement of NLG techniques guided by knowledge and reasoning. We also conclude by envisioning future directions and challenges in the pursuit of these goals.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 120 of its 156 references that are in the map. First posted on arXiv 7 Dec 2022.
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120 of 156 references.
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