Text Simplification
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Greatest papers with code
Query and Output: Generating Words by Querying Distributed Word Representations for Paraphrase Generation
The existing sequence-to-sequence model tends to memorize the words and the patterns in the training dataset instead of learning the meaning of the words.
ABSTRACTIVE TEXT SUMMARIZATION PARAPHRASE GENERATION TEXT SIMPLIFICATION WORD EMBEDDINGS
Optimizing Statistical Machine Translation for Text Simplification
Most recent sentence simplification systems use basic machine translation models to learn lexical and syntactic paraphrases from a manually simplified parallel corpus.
Exploring Neural Text Simplification Models
ACL 2017
• senisioi/NeuralTextSimplification
• 
Unlike the previously proposed automated TS systems, our neural text simplification (NTS) systems are able to simultaneously perform lexical simplification and content reduction.
LEXICAL SIMPLIFICATION MACHINE TRANSLATION TEXT SIMPLIFICATION WORD EMBEDDINGS
A Semantic Relevance Based Neural Network for Text Summarization and Text Simplification
• shumingma/SRB
• 
In this work, our goal is to improve semantic relevance between source texts and simplified texts for text summarization and text simplification.
SEMANTIC SIMILARITY SEMANTIC TEXTUAL SIMILARITY TEXT GENERATION TEXT SIMPLIFICATION TEXT SUMMARIZATION
EditNTS: An Neural Programmer-Interpreter Model for Sentence Simplification through Explicit Editing
We present the first sentence simplification model that learns explicit edit operations (ADD, DELETE, and KEEP) via a neural programmer-interpreter approach.
Unsupervised Neural Text Simplification
ACL 2019
• subramanyamdvss/UnsupNTS
• 
The paper presents a first attempt towards unsupervised neural text simplification that relies only on unlabeled text corpora.
Controllable Sentence Simplification
Text simplification aims at making a text easier to read and understand by simplifying grammar and structure while keeping the underlying information identical.
DiscoFuse: A Large-Scale Dataset for Discourse-Based Sentence Fusion
We author a set of rules for identifying a diverse set of discourse phenomena in raw text, and decomposing the text into two independent sentences.
Learning How to Simplify From Explicit Labeling of Complex-Simplified Text Pairs
Current research in text simplification has been hampered by two central problems: (i) the small amount of high-quality parallel simplification data available, and (ii) the lack of explicit annotations of simplification operations, such as deletions or substitutions, on existing data.
MACHINE TRANSLATION SENTENCE COMPRESSION TEXT SIMPLIFICATION