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Paraphrasing Revisited with Neural Machine Translation
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Paraphrasing Revisited with Neural Machine Translation
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Paraphrasing Revisited with Neural Machine Translation
Cite (ACL): Jonathan Mallinson, Rico Sennrich, and Mirella Lapata. 2017. Paraphrasing Revisited with Neural Machine Translation. In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers, pages 881-893, Valencia, Spain. Association for Computational Linguistics.
PDF Paraphrasing Revisited with Neural Machine Translation
Paraphrasing Revisited with Neural Machine Translation. Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers, pages 881-893, Valencia, Spain, April 3-7, 2017. c 2017 Association for Computational Linguistics. Paraphrasing Revisited with Neural Machine Translation.
Paraphrasing Revisited with Neural Machine Translation
In this paper we revisit bilingual pivoting in the context of neural machine translation and present a paraphrasing model based purely on neural networks. Our model represents paraphrases in a continuous space, estimates the degree of semantic relatedness between text segments of arbitrary length, or generates candidate paraphrases for any ...
Paraphrasing Revisited with Neural Machine Translation
This paper revisit bilingual pivoting in the context of neural machine translation and presents a paraphrasing model based purely on neural networks, which represents paraphrases in a continuous space, estimates the degree of semantic relatedness between text segments of arbitrary length, and generates candidate paraphrase for any source input. Recognizing and generating paraphrases is an ...
Paraphrasing Revisited with Neural Machine Translation
A well-established technique for automatically extracting paraphrases leverages bilingual corpora to find meaning-equivalent phrases in a single language by {``}pivoting {''} over a shared translation in another language. In this paper we revisit bilingual pivoting in the context of neural machine translation and present a paraphrasing model ...
Paraphrasing Revisited with Neural Machine Translation
Recently, Mallinson et al. (2017) revisited this method with neural machine translation to improve the paraphrase quality. Wieting and Gimpel (2018) leveraged bidirectional translation model to ...
Explorer Paraphrasing Revisited with Neural Machine Translation
This paper revisits bilingual pivoting in the context of neural machine translation and presents a paraphrasing model based purely on neural networks, showing that neural paraphrases outperform those obtained with conventional phrase-based pivoting approaches. Recognizing and generating paraphrases is an important component in many natural language processing applications. A wellestablished ...
Paraphrasing Revisited with Neural Machine Translation
DOI: 10.18653/V1/E17-1083 Corpus ID: 17246494; Paraphrasing Revisited with Neural Machine Translation @inproceedings{Lapata2017ParaphrasingRW, title={Paraphrasing Revisited with Neural Machine Translation}, author={Mirella Lapata and Rico Sennrich and Jonathan Mallinson}, booktitle={Conference of the European Chapter of the Association for Computational Linguistics}, year={2017} }
Paraphrasing Revisited with Neural Machine Translation
Paraphrasing Revisited with Neural Machine Translation. In Mirella Lapata , Phil Blunsom , Alexander Koller , editors, Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2017, Valencia, Spain, April 3-7, 2017, Volume 1: Long Papers .
(PDF) Improving the Diversity of Unsupervised Paraphrasing with
Paraphrasing revisited with neural machine translation. In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers, pages 881-893. Jonathan Mallinson, Rico Sennrich, and Mirella Lapata. 2017b. Paraphrasing revisited with neural machine translation.
ParaNMT-50M: Pushing the Limits of Paraphrastic Sentence ...
The method was revisited using neural machine translation to improve the quality of paraphrase generation. Following this, some works have utilized bidirectional translation models to construct ...
(PDF) Pushing the Limits of Paraphrastic Sentence Embeddings with
Paraphrasing Revisited with Neural Machine Translation. Conference Paper. Jan 2017; ... In the process, we explore how neural machine translation output differs from human-written sentences ...
Paraphrases as Foreign Languages in Multilingual Neural Machine Translation
Paraphrases, the rewordings of the same semantic meaning, are useful for improving generalization and translation. However, prior works only explore paraphrases at the word or phrase level, not at the sentence or corpus level. Unlike previous works that only explore paraphrases at the word or phrase level, we use different translations of the whole training data that are consistent in ...
PDF Edinburgh Research Explorer
Paraphrasing Revisited with Neural Machine Translation Jonathan Mallinson, Rico Sennrich and Mirella Lapata Institute for Language, Cognition and Computation School of Informatics, University of Edinburgh 10 Crichton Street, Edinburgh EH8 9AB [email protected], frsennric,[email protected] Abstract Recognizing and generating paraphrases is
Neural machine translation: A review of methods, resources, and tools
Machine translation (MT) is an important sub-field of natural language processing that aims to translate natural languages using computers. In recent years, end-to-end neural machine translation (NMT) has achieved great success and has become the new mainstream method in practical MT systems. In this article, we first provide a broad review of ...
Augmenting Paraphrase Generation with Syntax Information Using Graph
Recent years have witnessed great successes in neural machine translation (NMT) and related generation tasks that could be formulated under the sequence-to-sequence learning framework. ... Mallinson J., Sennrich R., Lapata M. Paraphrasing Revisited with Neural Machine Translation; Proceedings of the 15th Conference of the European Chapter of ...
Improving paraphrase generation using supervised neural-based
In phrase generation (PG), a sentence in the natural language is changed into a new one with a different syntactic structure but having the same semantic meaning. The present sequence-to-sequence strategy aims to recall the words and structures from the training dataset rather than learning the words' semantics. As a result, the resulting statements are frequently grammatically accurate but ...
Paraphrasing Revisited with Neural Machine Translation
From this combined distribution a word is chosen, which is then given as input to each decoder. - "Paraphrasing Revisited with Neural Machine Translation" Figure 1: Late-weighted combination: two pivot sentences are simultaneously translated to one target sentence. Blue circles indicate the encoders, which individually encode the two source ...
Document-level paraphrase generation base on attention enhanced graph
In addition, there is a method of paraphrase generation through "rotation", which uses reverse machine translation to increase diversity. Recently, the method has been put through a series of optimisations . The method was revisited using neural machine translation to improve the quality of paraphrase generation.
Paraphrase Generation as Zero-Shot Multilingual Translation
A simple paraphrase generation algorithm which discourages the production of n-grams that are present in the input and which produces paraphrases that better preserve meaning and are more gramatical, for the same level of lexical diversity. Recent work has shown that a multilingual neural machine translation (NMT) model can be used to judge how well a sentence paraphrases another sentence in ...
Paraphrase Generation: A Review from RNN to Transformer based
Paraphrasing revisited with neural machine translation. In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics. Association for Computational Linguistics, Valencia, Spain, 881-893.
This work confirms the finding that paraphrased references yield metric scores that correlate better with human judgment, and demonstrates for the first time that using these scores for system development can lead to significant improvements. Automatic evaluation comparing candidate translations to human-generated paraphrases of reference translations has recently been proposed by ...
Generating Phrasal and Sentential Paraphrases: A ...
Paraphrasing Revisited with Neural Machine Translation. Mirella Lapata Rico Sennrich Jonathan Mallinson. Computer Science, Linguistics. EACL. 2017; TLDR. This paper revisit bilingual pivoting in the context of neural machine translation and presents a paraphrasing model based purely on neural networks, which represents paraphrases in a ...
IMAGES
VIDEO
COMMENTS
Cite (ACL): Jonathan Mallinson, Rico Sennrich, and Mirella Lapata. 2017. Paraphrasing Revisited with Neural Machine Translation. In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers, pages 881-893, Valencia, Spain. Association for Computational Linguistics.
Paraphrasing Revisited with Neural Machine Translation. Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers, pages 881-893, Valencia, Spain, April 3-7, 2017. c 2017 Association for Computational Linguistics. Paraphrasing Revisited with Neural Machine Translation.
In this paper we revisit bilingual pivoting in the context of neural machine translation and present a paraphrasing model based purely on neural networks. Our model represents paraphrases in a continuous space, estimates the degree of semantic relatedness between text segments of arbitrary length, or generates candidate paraphrases for any ...
This paper revisit bilingual pivoting in the context of neural machine translation and presents a paraphrasing model based purely on neural networks, which represents paraphrases in a continuous space, estimates the degree of semantic relatedness between text segments of arbitrary length, and generates candidate paraphrase for any source input. Recognizing and generating paraphrases is an ...
A well-established technique for automatically extracting paraphrases leverages bilingual corpora to find meaning-equivalent phrases in a single language by {``}pivoting {''} over a shared translation in another language. In this paper we revisit bilingual pivoting in the context of neural machine translation and present a paraphrasing model ...
Recently, Mallinson et al. (2017) revisited this method with neural machine translation to improve the paraphrase quality. Wieting and Gimpel (2018) leveraged bidirectional translation model to ...
This paper revisits bilingual pivoting in the context of neural machine translation and presents a paraphrasing model based purely on neural networks, showing that neural paraphrases outperform those obtained with conventional phrase-based pivoting approaches. Recognizing and generating paraphrases is an important component in many natural language processing applications. A wellestablished ...
DOI: 10.18653/V1/E17-1083 Corpus ID: 17246494; Paraphrasing Revisited with Neural Machine Translation @inproceedings{Lapata2017ParaphrasingRW, title={Paraphrasing Revisited with Neural Machine Translation}, author={Mirella Lapata and Rico Sennrich and Jonathan Mallinson}, booktitle={Conference of the European Chapter of the Association for Computational Linguistics}, year={2017} }
Paraphrasing Revisited with Neural Machine Translation. In Mirella Lapata , Phil Blunsom , Alexander Koller , editors, Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2017, Valencia, Spain, April 3-7, 2017, Volume 1: Long Papers .
Paraphrasing revisited with neural machine translation. In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers, pages 881-893. Jonathan Mallinson, Rico Sennrich, and Mirella Lapata. 2017b. Paraphrasing revisited with neural machine translation.
The method was revisited using neural machine translation to improve the quality of paraphrase generation. Following this, some works have utilized bidirectional translation models to construct ...
Paraphrasing Revisited with Neural Machine Translation. Conference Paper. Jan 2017; ... In the process, we explore how neural machine translation output differs from human-written sentences ...
Paraphrases, the rewordings of the same semantic meaning, are useful for improving generalization and translation. However, prior works only explore paraphrases at the word or phrase level, not at the sentence or corpus level. Unlike previous works that only explore paraphrases at the word or phrase level, we use different translations of the whole training data that are consistent in ...
Paraphrasing Revisited with Neural Machine Translation Jonathan Mallinson, Rico Sennrich and Mirella Lapata Institute for Language, Cognition and Computation School of Informatics, University of Edinburgh 10 Crichton Street, Edinburgh EH8 9AB [email protected], frsennric,[email protected] Abstract Recognizing and generating paraphrases is
Machine translation (MT) is an important sub-field of natural language processing that aims to translate natural languages using computers. In recent years, end-to-end neural machine translation (NMT) has achieved great success and has become the new mainstream method in practical MT systems. In this article, we first provide a broad review of ...
Recent years have witnessed great successes in neural machine translation (NMT) and related generation tasks that could be formulated under the sequence-to-sequence learning framework. ... Mallinson J., Sennrich R., Lapata M. Paraphrasing Revisited with Neural Machine Translation; Proceedings of the 15th Conference of the European Chapter of ...
In phrase generation (PG), a sentence in the natural language is changed into a new one with a different syntactic structure but having the same semantic meaning. The present sequence-to-sequence strategy aims to recall the words and structures from the training dataset rather than learning the words' semantics. As a result, the resulting statements are frequently grammatically accurate but ...
From this combined distribution a word is chosen, which is then given as input to each decoder. - "Paraphrasing Revisited with Neural Machine Translation" Figure 1: Late-weighted combination: two pivot sentences are simultaneously translated to one target sentence. Blue circles indicate the encoders, which individually encode the two source ...
In addition, there is a method of paraphrase generation through "rotation", which uses reverse machine translation to increase diversity. Recently, the method has been put through a series of optimisations . The method was revisited using neural machine translation to improve the quality of paraphrase generation.
A simple paraphrase generation algorithm which discourages the production of n-grams that are present in the input and which produces paraphrases that better preserve meaning and are more gramatical, for the same level of lexical diversity. Recent work has shown that a multilingual neural machine translation (NMT) model can be used to judge how well a sentence paraphrases another sentence in ...
Paraphrasing revisited with neural machine translation. In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics. Association for Computational Linguistics, Valencia, Spain, 881-893.
This work confirms the finding that paraphrased references yield metric scores that correlate better with human judgment, and demonstrates for the first time that using these scores for system development can lead to significant improvements. Automatic evaluation comparing candidate translations to human-generated paraphrases of reference translations has recently been proposed by ...
Paraphrasing Revisited with Neural Machine Translation. Mirella Lapata Rico Sennrich Jonathan Mallinson. Computer Science, Linguistics. EACL. 2017; TLDR. This paper revisit bilingual pivoting in the context of neural machine translation and presents a paraphrasing model based purely on neural networks, which represents paraphrases in a ...