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The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics
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In: Proceedings of the 1st Workshop on Natural Language Generation, Evaluation, and Metrics (GEM 2021) ; https://hal.archives-ouvertes.fr/hal-03466171 ; Proceedings of the 1st Workshop on Natural Language Generation, Evaluation, and Metrics (GEM 2021), Aug 2021, Online, France. pp.96-120, ⟨10.18653/v1/2021.gem-1.10⟩ (2021)
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The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics ...
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A Thorough Evaluation of Task-Specific Pretraining for Summarization ...
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MiRANews: Dataset and Benchmarks for Multi-Resource-Assisted News Summarization ...
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Leveraging Pre-trained Checkpoints for Sequence Generation Tasks
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In: Transactions of the Association for Computational Linguistics, Vol 8, Pp 264-280 (2020) (2020)
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Privacy-preserving Neural Representations of Text
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In: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing ; 2018 Conference on Empirical Methods in Natural Language Processing ; https://hal.archives-ouvertes.fr/hal-02135081 ; 2018 Conference on Empirical Methods in Natural Language Processing, Nov 2018, Brussels, Belgium. pp.1--10 (2018)
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Split and Rephrase
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In: EMNLP 2017: Conference on Empirical Methods in Natural Language Processing ; https://hal.inria.fr/hal-01623746 ; EMNLP 2017: Conference on Empirical Methods in Natural Language Processing, Sep 2017, Copenhagen, Denmark. pp.617 - 627 (2017)
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The WebNLG Challenge: Generating Text from RDF Data
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In: Proceedings of the 10th International Conference on Natural Language Generation ; https://hal.archives-ouvertes.fr/hal-02461197 ; Proceedings of the 10th International Conference on Natural Language Generation, Sep 2017, Santiago de Compostela, Spain. pp.124-133, ⟨10.18653/v1/W17-3518⟩ (2017)
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Abstract:
International audience ; The WebNLG challenge consists in mapping sets of RDF triples to text. It provides a common benchmark on which to train, evaluate and compare “microplanners”, i.e. generation systems that verbalise a given content by making a range of complex interacting choices including referring expression generation, aggregation, lexicalisation, surface realisation and sentence segmentation. In this paper, we introduce the microplanning task, describe data preparation, introduce our evaluation methodology, analyse participant results and provide a brief description of the participating systems.
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Keyword:
[INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]
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URL: https://hal.archives-ouvertes.fr/hal-02461197 https://doi.org/10.18653/v1/W17-3518
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Creating Training Corpora for NLG Micro-Planning
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In: 55th annual meeting of the Association for Computational Linguistics (ACL) ; https://hal.inria.fr/hal-01623744 ; 55th annual meeting of the Association for Computational Linguistics (ACL), Jul 2017, Vancouver, Canada (2017)
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The SUMMA Platform Prototype
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In: http://infoscience.epfl.ch/record/233575 (2017)
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Paraphrase Generation from Latent-Variable PCFGs for Semantic Parsing ...
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