[PDF] Top 20 Neural Paraphrase Generation using Transfer Learning
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Neural Paraphrase Generation using Transfer Learning
... Sentential paraphrase corpora are pro- hibitively small for training large neural networks, but textual entailment corpora are quite large thanks to the SNLI ...performing transfer learning ... See full document
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Neural Paraphrase Generation with Stacked Residual LSTM Networks
... of learning on a limited ...training paraphrase generation ...during paraphrase generation, which is a notable limitation of the existing paraphrase evaluation ... See full document
12
Exploring Diverse Expressions for Paraphrase Generation
... deep neural models have also been applied to paraphrase generation due to their great success on natural language processing ...controlled paraphrase, Li et ...text generation A few ... See full document
10
Stylistic Transfer in Natural Language Generation Systems Using Recurrent Neural Networks
... propose using phrase-based machine translation sys- tems to carry out paraphrasing while targeting a par- ticular writing ...of neural machine translation by adding side ... See full document
5
Negative Lexically Constrained Decoding for Paraphrase Generation
... Paraphrase generation can be regarded as monolingual ...translation, paraphrase generation rewrites only a limited portion of an input ...a neural model for paraphrase ... See full document
6
An Empirical Comparison on Imitation Learning and Reinforcement Learning for Paraphrase Generation
... text generation (Radford et ...phrase generation is mainly from neural net- work modeling (Prakash et ...corresponding paraphrase for each input ... See full document
7
Paraphrase Generation for Semi Supervised Learning in NLU
... that neural machine transla- tion (NMT) systems perform better than phrase- based MT systems in paraphrase generation ...phrase generation using the transformer leads to better ... See full document
10
Controllable Paraphrase Generation with a Syntactic Exemplar
... multi-task learning objectives that make use of paraphrases and word order infor- ...the learning of syntax, we additionally propose to train the syntactic com- ponent of our model with word noising and ... See full document
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Paraphrase Generation with Deep Reinforcement Learning
... Neural paraphrase generation recently draws at- tention in different application ...controllable paraphrase gen- ...reinforcement learning, in which the reward function is manually ... See full document
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Decomposable Neural Paraphrase Generation
... multi-task learning (MTL) (Domhan and Hieber, 2017) that harness the non-parallel data in the target domain for ...general paraphrase patterns and meanwhile avoid mistakes on rephrasing domain-specific ... See full document
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Neural Clinical Paraphrase Generation with Attention
... particular, paraphrase generation has a significant value in developing patient-centric intelligent clinical decision support (CDS) applications where users are able to understand complex clinical jargons ... See full document
12
Convolutional Neural Network for Paraphrase Identification
... deep learning architecture Bi- CNN-MI for paraphrase identification ...representations using convo- lution and compute interaction feature matrices at each ... See full document
11
Vision based human action recognition using machine learning techniques
... In recent years, various methods have been published for multiview action recognition, but very few are actually suitable for real-time applications due to their high computa- tional cost. Therefore, the cost of the ... See full document
173
Monolingual Machine Translation for Paraphrase Generation
... Our training corpus, like those of Shinyama et al. and Barzilay & Lee, consists of different news stories reporting the same event. While previous work with comparable news corpora has been lim- ited to just two news ... See full document
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Transformer and seq2seq model for Paraphrase Generation
... pable of generating novel words, it also learns to compress or remove unnecessary words along the way. Thus, gainfully lending itself to ab- stractive summarization (Chen and Bansal, 2018; Gehrmann et al., 2018) and ... See full document
7
Hierarchy Response Learning for Neural Conversation Generation
... In our work, a CNN module is leveraged to fil- ter the content-related information of utterances and get a discourse-level representation, i.e. ex- pression vector, where meaningful expression in- formation is preserved. ... See full document
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Creating and using large monolingual parallel corpora for sentential paraphrase generation
... sentential paraphrase generation, because no exhaustive list of paraphrases can exist (Madnani and Dorr, ...sentential paraphrase generation method given unseen ...in paraphrase ... See full document
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Paraphrase Recognition Using Machine Learning to Combine Similarity Measures
... A paraphrase gener- ator, meaning a module that produces new phrases or patterns that are semantically equivalent (or al- most equivalant) to a given input phrase or pattern ... See full document
9
Learning to Control the Specificity in Neural Response Generation
... There have been a few efforts attempting to ad- dress this issue in literature. Li et al. (2016a) proposed to use the Maximum Mutual Informa- tion (MMI) as the objective to penalize general re- sponses. It could be ... See full document
10
Learning to Paraphrase: An Unsupervised Approach Using Multiple Sequence Alignment
... Our work presents a novel knowledge-lean algorithm that uses multiple-sequence alignment (MSA) to learn to generate sentence-level paraphrases essentially from unannotated corpus data alone. In contrast to previ- ous ... See full document
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