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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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Pre-train or Annotate? Domain Adaptation with a Constrained Budget ...
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BiSECT: Learning to Split and Rephrase Sentences with Bitexts ...
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Abstract:
Anthology paper link: https://aclanthology.org/2021.emnlp-main.500/ Abstract: An important task in NLP applications such as sentence simplification is the ability to take a long, complex sentence and split it into shorter sentences, rephrasing as necessary. We introduce a novel dataset and a new model for this `split and rephrase' task. Our BiSECT training data consists of 1 million long English sentences paired with shorter, meaning-equivalent English sentences. We obtain these by extracting 1-2 sentence alignments in bilingual parallel corpora and then using machine translation to convert both sides of the corpus into the same language. BiSECT contains higher quality training examples than previous Split and Rephrase corpora, with sentence splits that require more significant modifications. We categorize examples in our corpus, and use these categories in a novel model that allows us to target specific regions of the input sentence to be split and edited. Moreover, we show that models trained on BiSECT can ...
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Keyword:
Computational Linguistics; Machine Learning; Machine Learning and Data Mining; Natural Language Processing
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URL: https://underline.io/lecture/37931-bisect-learning-to-split-and-rephrase-sentences-with-bitexts https://dx.doi.org/10.48448/98n6-k286
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Sample data for "Design and Collection Challenges of Building an Academic Email Corpus for Linguistics and Computational Research" ...
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Sample data for "Design and Collection Challenges of Building an Academic Email Corpus for Linguistics and Computational Research" ...
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Controllable Text Simplification with Explicit Paraphrasing ...
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The effectiveness of the problem-based learning in medical cell biology education: A systematic meta-analysis
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In: Medicine (Baltimore) (2021)
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Controllable text simplification with explicit paraphrasing
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An Empirical Study of Pre-trained Transformers for Arabic Information Extraction ...
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Controllable Text Simplification with Explicit Paraphrasing ...
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Interactive Grounded Language Acquisition and Generalization in a 2D World ...
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Interactive Language Acquisition with One-shot Visual Concept Learning through a Conversational Game ...
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Guided Feature Transformation (GFT): A Neural Language Grounding Module for Embodied Agents ...
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A Word-Complexity Lexicon and A Neural Readability Ranking Model for Lexical Simplification ...
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A Deep Compositional Framework for Human-like Language Acquisition in Virtual Environment ...
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A Continuously Growing Dataset of Sentential Paraphrases ...
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Spectral Entropy Can Predict Changes of Working Memory Performance Reduced by Short-Time Training in the Delayed-Match-to-Sample Task
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