[PDF] Top 20 Exploring Neural Text Simplification Models
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Exploring Neural Text Simplification Models
... (PBSMT) models (Spe- cia, 2010; ˇStajner et ...cal simplification (LS) was addressed by unsuper- vised approaches leveraging word-embeddings, with reported good success (Glavaˇs and ˇStajner, 2015; Paetzold ... See full document
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Neural Text Simplification in Low Resource Conditions Using Weak Supervision
... When concatenating all the synthetic and real data, and the pre-trained embeddings are used, the performance is comparable with the one obtained using the simple-to-complex synthetic pairs, but at the cost of using a ... See full document
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Metaphors in Text Simplification: To change or not to change, that is the question
... Lexical simplification systems often build on sentence-aligned simplification corpora and pro- pose substitutes for complex words from a num- ber of synonyms based on the words’ frequency, length and ... See full document
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Sentence Simplification with Memory Augmented Neural Networks
... of neural MT (Sutskever et ...started exploring neural simplification with sequence to sequence (Seq2seq) models, also referred to as encoder-decoder ... See full document
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Text Simplification as Tree Labeling
... Several approaches to sentence compression have been presented in the last decade. Knight and Marcu (2002) and Turner and Charniak (2005) ap- ply noisy channel models, using language models to control for ... See full document
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Data Driven Text Simplification
... systems exploring various deep learning architectures appeared, using the new alignments of Wikipedia and Newsela for ...Sequence-to-sequence neural models (Nisioi et ...the neural model based ... See full document
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Understanding Neural Machine Translation by Simplification: The Case of Encoder-free Models
... The attention mechanism has been introduced as a way to learn an alignment between the source and target text, and improves encoder-decoder models significantly, while also providing a way to inter- pret ... See full document
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Neural Text Simplification of Clinical Letters with a Domain Specific Phrase Table
... The text it produced was gener- ally much longer than the original ...the neural text simplification software, which is capable of applying the phrase table at the correct points in the ... See full document
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A Closer Look at Data Bias in Neural Extractive Summarization Models
... Recently, neural network-based models have achieved great success in extractive ...on text summarization can roughly fall into one of three classes: exploring networks’ structures with ... See full document
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A Detailed Evaluation of Neural Sequence to Sequence Models for In domain and Cross domain Text Simplification
... of neural sequence-to-sequence models in TS (Nisioi et ...our simplification sys- tems are based on neural networks (Graves, 2012) with global attention in combination with input feeding ... See full document
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Unsupervised Neural Text Simplification
... SARI (Xu et al., 2016) is an automatic evalua- tion metric designed to measure the simpleness of the generated sentences. SARI requires access to source, predictions and references for evaluation. Computing SARI involves ... See full document
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Simple and Effective Text Simplification Using Semantic and Neural Methods
... structural simplification and statistical methods for lexical ...Lexical simplification is performed using the Moses sys- ...Lexical simplification is there performed us- ing the unsupervised model ... See full document
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Exploring Verb Frames for Sentence Simplification in Hindi
... sentence simplification. Automatic induction of rules for text simplification is discussed by Chan- drashekhar and Srinivas ...for text simplification has been presented by ... See full document
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Optimizing Statistical Machine Translation for Text Simplification
... phrasing models for text simplification — most pre- vious work has used off-the-shelf statistical machine translation (SMT) technology and achieved reason- able results (Coster and Kauchak, 2011a,b; ... See full document
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Text Simplification from Professionally Produced Corpora
... in Text Simplification ...learning models to classify sentences into complex ...sentence simplification patterns in more effective ways than corpora used in previous ... See full document
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Unified Framework For Deep Learning Based Text Classification
... data. Text data is generated from various channels including web repositories, blogs, news feeds ...recognition, text classification etc. Text classification is an example of supervised machine ... See full document
5
Text Simplification Based On Lexical Analysis
... performs text simplification using synchronous dependency ...lexical simplification rules can be generalised to enable their application in new contexts without introducing errors, and an evaluation ... See full document
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A Hybrid System for Spanish Text Simplification
... Automatic text simplification is the process by which a computer transforms a text for a particular readership into an adapted version which is easier to read than the ...assistive text ... See full document
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HIPAA Administrative Simplification. Regulation Text
... Except with respect to uses or disclosures that require an authorization under §164.508(a)(2) and (3), a covered entity may use or disclose protected health information for treatment,[r] ... See full document
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Globally Coherent Text Generation with Neural Checklist Models
... recipe text and the ingredient ...recipe text from the training data (i.e., the text of the recipe not including the title or ingredient list) has 14,103 unique ... See full document
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