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The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics
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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3
Neural semi-Markov CRF for Monolingual Word Alignment ...
Lan, Wuwei; Jiang, Chao; Xu, Wei. - : arXiv, 2021
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4
Pre-train or Annotate? Domain Adaptation with a Constrained Budget ...
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5
Neural semi-Markov CRF for Monolingual Word Alignment ...
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6
BiSECT: Learning to Split and Rephrase Sentences with Bitexts ...
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7
Sample data for "Design and Collection Challenges of Building an Academic Email Corpus for Linguistics and Computational Research" ...
Diaz, Damian Yukio Romero; Hanyu Jia; Xu, Wei. - : University of Arizona Research Data Repository, 2021
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Sample data for "Design and Collection Challenges of Building an Academic Email Corpus for Linguistics and Computational Research" ...
Romero Diaz, Damian Yukio; Jia, Hanyu; Xu, Wei. - : University of Arizona Research Data Repository, 2021
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9
Controllable Text Simplification with Explicit Paraphrasing ...
NAACL 2021 2021; Alva-Manchego, Fernando; Maddela, Mounica; Xu, Wei. - : Underline Science Inc., 2021
Abstract: Read the paper on the folowing link: https://www.aclweb.org/anthology/2021.naacl-main.277/ Abstract: Text Simplification improves the readability of sentences through several rewriting transformations, such as lexical paraphrasing, deletion, and splitting. Current simplification systems are predominantly sequence-to-sequence models that are trained end-to-end to perform all these operations simultaneously. However, such systems limit themselves to mostly deleting words and cannot easily adapt to the requirements of different target audiences. In this paper, we propose a novel hybrid approach that leverages linguistically motivated rules for splitting and deletion, and couples them with a neural paraphrasing model to produce varied rewriting styles. We introduce a new data augmentation method to improve the paraphrasing capability of our model. Through automatic and manual evaluations, we show that our proposed model establishes a new state-of-the-art for the task, paraphrasing more often than the existing ...
Keyword: Artificial Intelligence; Computer Science and Engineering; Intelligent System; Natural Language Processing
URL: https://dx.doi.org/10.48448/ze3t-sa51
https://underline.io/lecture/19581-controllable-text-simplification-with-explicit-paraphrasing
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10
The effectiveness of the problem-based learning in medical cell biology education: A systematic meta-analysis
In: Medicine (Baltimore) (2021)
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11
Controllable text simplification with explicit paraphrasing
Maddela, Mounica; Alva-Manchego, Fernando; Xu, Wei. - : Association for Computational Linguistics, 2021
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12
An Empirical Study of Pre-trained Transformers for Arabic Information Extraction ...
Lan, Wuwei; Chen, Yang; Xu, Wei. - : arXiv, 2020
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13
Controllable Text Simplification with Explicit Paraphrasing ...
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14
Interactive Grounded Language Acquisition and Generalization in a 2D World ...
Yu, Haonan; Zhang, Haichao; Xu, Wei. - : arXiv, 2018
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15
Interactive Language Acquisition with One-shot Visual Concept Learning through a Conversational Game ...
Zhang, Haichao; Yu, Haonan; Xu, Wei. - : arXiv, 2018
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16
Guided Feature Transformation (GFT): A Neural Language Grounding Module for Embodied Agents ...
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17
A Word-Complexity Lexicon and A Neural Readability Ranking Model for Lexical Simplification ...
Maddela, Mounica; Xu, Wei. - : arXiv, 2018
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18
A Deep Compositional Framework for Human-like Language Acquisition in Virtual Environment ...
Yu, Haonan; Zhang, Haichao; Xu, Wei. - : arXiv, 2017
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19
A Continuously Growing Dataset of Sentential Paraphrases ...
Lan, Wuwei; Qiu, Siyu; He, Hua. - : arXiv, 2017
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20
Spectral Entropy Can Predict Changes of Working Memory Performance Reduced by Short-Time Training in the Delayed-Match-to-Sample Task
Tian, Yin; Zhang, Huiling; Xu, Wei. - : Frontiers Media S.A., 2017
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