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Concept-To-Text Generation

Generating natural language text from a conceptualized representation, such as an ontology.

Papers

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Showing 1–17 of 17 papers

TitleStatusHype
Visualize Before You Write: Imagination-Guided Open-Ended Text GenerationCode1
Deep Attentive Sentence Ordering Network—0
Discourse Planning with an N-gram Model of Relations—0
Enhancing Topic-to-Essay Generation with External Commonsense Knowledge—0
Extracting Linguistic Resources from the Web for Concept-to-Text Generation—0
Informed Sampling for Diversity in Concept-to-Text NLG—0
Generating Texts with Integer Linear Programming—0
Inducing Document Plans for Concept-to-Text Generation—0
Concept-to-text Generation via Discriminative Reranking—0
Retrieve, Caption, Generate: Visual Grounding for Enhancing Commonsense in Text Generation Models—0
SAPPHIRE: Approaches for Enhanced Concept-to-Text Generation—0
Surface Realisation from Knowledge-Bases—0
TUDA-Reproducibility @ ReproGen: Replicability of Human Evaluation of Text-to-Text and Concept-to-Text Generation—0
Unsupervised Concept-to-text Generation with Hypergraphs—0
Using Integer Linear Programming in Concept-to-Text Generation to Produce More Compact Texts—0
Learning to Order Natural Language Texts—0
Neural Text Generation from Structured Data with Application to the Biography DomainCode0
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