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Neural Methods for Data-to-text Generation

delete2024-10-17
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OA
AI
M
Mandar Sharma *
A
Ajay Kumar Gogineni
N
Naren Ramakrishnan
DOI：10.1145/3660639delete
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Abstract

Abstract

En 中文
The neural boom that has sparked natural language processing (NLP) research throughout the last decade has similarly led to significant innovations in data-to-text (D2T) generation. This survey offers a consolidated view into the neural D2T paradigm with a structured examination of the approaches, benchmark datasets, and evaluation protocols. This survey draws boundaries separating D2T from the rest of the natural language generation (NLG) landscape, encompassing an up-to-date synthesis of the literature, and highlighting the stages of technological adoption from within and outside the greater NLG umbrella. With this holistic view, we highlight promising avenues for D2T research that focus not only on the design of linguistically capable systems but also on systems that exhibit fairness and accountability.
Keywords:
Narration
data-to-text
data-to-text generation
natural language genera- tion

Journal

ACM Transactions on Intelligent Systems and Technology cover
ACM Transactions on Intelligent Systems and Technology
IF:
6.6
Papers:
1.5K
Citations:
6.2K

Organization

No organization information available