2020: Evaluating the state-of-the-art of End-to-End Natural Language Generation: The E2E NLG challenge

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2026-10-10

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   E2E github.com

   This shared task focuses on recent end-to-end (E2E), data-driven NLG methods, which jointly learn sentence planning and surface realisation from non-aligned data.

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   2020: Natural language generation: The commercial state ofthe art in 2020 cambridge.org

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   2017: Survey of the State of the Art in NaturalLanguage Generation: Core tasks, applicationsand evaluation arxiv.org

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   NLG-eval github.com

   Evaluation code for various unsupervised automated metrics for Natural Language Generation.

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   2021: Vision: NLG Can Help Humanise Data and AI ehudreiter.com

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   2016: Natural Language Generation enhances human decision-making with uncertain information arxiv.org

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