[PDF] Top 20 Lexical Simplification with Neural Ranking
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Lexical Simplification with Neural Ranking
... in simplification, but thus far no sim- plifiers exist that exploit this ...using Neural Network approaches, which have proved promising for many related ...problems. Neural Networks for supervised ... See full document
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Lexical Simplification with the Deep Structured Similarity Model
... The ranking step is challenging because the sub- stitution candidates usually have similar meaning to the target word, and thus share similar con- text ...in lexical simplification exploit supervised ... See full document
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Metaheuristic Approaches to Lexical Substitution and Simplification
... and ranking them relatively ...three ranking methods are doing more or less the same thing, at least for the first few ...n-gram–based ranking model was attempting to ... See full document
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Recursive Context Aware Lexical Simplification
... Following substitute generation, the next step in the LS pipeline is to choose one of the generated candidates to replace the original target word. This is done by filtering and ranking the candidates us- ing a ... See full document
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SimpleScience: Lexical Simplification of Scientific Terminology
... prior ranking meth- ods used in Lexenstein (Paetzold and Specia, 2015), with the exception of using machine learning tech- niques like SVM (Paetzold and Specia, ...interactive simplification suggestion ... See full document
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Controllable Text Simplification with Lexical Constraint Loss
... Text simplification can be regarded as a mono- lingual machine translation problem. Previ- ous studies have trained a model to trans- late complex sentences into simpler sentences on parallel corpora between ... See full document
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Controlled and Balanced Dataset for Japanese Lexical Simplification
... English lexical simplifi- cation based on that developed by McCarthy and Navigli ...of lexical simplification be- cause the human ranking of the resulting simpli- fication might be affected by ... See full document
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CEFR based Lexical Simplification Dataset
... in lexical simplification for selecting the correct candidate using statistical and ma- chine learning methods such as Support Vector Machines (Horn et ...2014), neural networks (Paetzold and Specia, ... See full document
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Unsupervised Neural Text Simplification
... towards lexical and syntactic simplification and are lim- ited to splitting and/or truncating ...based simplification, data-driven ap- proaches were proposed like phrase-based SMT (Specia, 2010; ... See full document
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Simplification Using Paraphrases and Context Based Lexical Substitution
... the lexical simplification subtask, existing methods differ in their decision to include a word sense disambiguation (WSD) step for substitute selection and in the ranking method ...learn ... See full document
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Out in the Open: Finding and Categorising Errors in the Lexical Simplification Pipeline
... typical lexical simplification system follows the pipeline shown in Figure ...the lexical sim- plification ...other simplification systems may not have explicitly followed the pipeline shown ... See full document
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Sentence Simplification with Memory Augmented Neural Networks
... of neural MT (Sutskever et ...exploring neural simplification with sequence to sequence (Seq2seq) models, also referred to as encoder-decoder ...unsupervised lexical simplifi- cation ... See full document
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Evaluation Dataset and System for Japanese Lexical Simplification
... on the average of the rank from each annota- tor, following the previous research (Specia et al., 2012). The same rank is assigned to words that have the same average. In this study, the same annotator performed both the ... See full document
6
Benchmarking Lexical Simplification Systems
... Boundary Ranking approach of (Paetzold and Specia, 2016) offers an effective solution to Substitution Selection ...Substitution Ranking, supervised techniques seem to be the most ... See full document
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A Word Complexity Lexicon and A Neural Readability Ranking Model for Lexical Simplification
... the lexical and phrasal paraphrase rules in the Para- phrase Database (PPDB) (Pavlick et ...resulting lexical resource, Sim- plePPDB++, contains all 13.1 million lexical and phrasal paraphrase rules ... See full document
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Reliable Lexical Simplification for Non Native Speakers
... to optimize not the correlation between the learned rankings and the gold-standard, but instead the like- lihood of the best candidate substitution to be ranked first. We can also notice from the results that, when ... See full document
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LEXenstein: A Framework for Lexical Simplification
... We have presented LEXenstein, a framework for Lexical Simplification distributed under the per- missive BSD license. It provides a wide arrange of useful resources and tools for the task, such as feature ... See full document
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Personalized Substitution Ranking for Lexical Simplification
... Substitution Ranking algorithm that optimizes the trade-off be- tween semantic faithfulness and word complexity for the lexical simplification (LS) task, by select- ing the non-complex candidate that ... See full document
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Text simplification using synchronous dependency grammars: Generalising automatically harvested rules
... syntactic simplification (as described in Sid- dharthan (2011)), we filter out rules that involve dependency relations for passive voice, relative clauses, apposition, coordination and subordina- ...single ... See full document
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Exploring Neural Text Simplification Models
... 2015). Neural machine translation (Cho et ...2010), neural networks are being trained end-to-end, without the need to have external de- coders, language models or phrase ... See full document
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