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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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BiSECT: Learning to Split and Rephrase Sentences with Bitexts ...
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The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics ...
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BiSECT: Learning to Split and Rephrase Sentences with Bitexts ...
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Controllable Text Simplification with Explicit Paraphrasing ...
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Controllable Text Simplification with Explicit Paraphrasing ...
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A Word-Complexity Lexicon and A Neural Readability Ranking Model for Lexical Simplification ...
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Abstract:
Current lexical simplification approaches rely heavily on heuristics and corpus level features that do not always align with human judgment. We create a human-rated word-complexity lexicon of 15,000 English words and propose a novel neural readability ranking model with a Gaussian-based feature vectorization layer that utilizes these human ratings to measure the complexity of any given word or phrase. Our model performs better than the state-of-the-art systems for different lexical simplification tasks and evaluation datasets. Additionally, we also produce SimplePPDB++, a lexical resource of over 10 million simplifying paraphrase rules, by applying our model to the Paraphrase Database (PPDB). ... : 12 pages; EMNLP 2018 ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences
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URL: https://dx.doi.org/10.48550/arxiv.1810.05754 https://arxiv.org/abs/1810.05754
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