Browse > Natural Language Processing > Text Simplification

Text Simplification

18 papers with code · Natural Language Processing

Leaderboards

No evaluation results yet. Help compare methods by submit evaluation metrics.

Greatest papers with code

Query and Output: Generating Words by Querying Distributed Word Representations for Paraphrase Generation

NAACL 2018 lancopku/WEAN

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

TACL 2016 cocoxu/simplification

Most recent sentence simplification systems use basic machine translation models to learn lexical and syntactic paraphrases from a manually simplified parallel corpus.

MACHINE TRANSLATION TEXT SIMPLIFICATION

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

6 Oct 2017shumingma/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

ACL 2019 yuedongP/EditNTS

We present the first sentence simplification model that learns explicit edit operations (ADD, DELETE, and KEEP) via a neural programmer-interpreter approach.

MACHINE TRANSLATION TEXT SIMPLIFICATION

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.

DENOISING TEXT SIMPLIFICATION

Controllable Sentence Simplification

LREC 2020 facebookresearch/access

Text simplification aims at making a text easier to read and understand by simplifying grammar and structure while keeping the underlying information identical.

TEXT SIMPLIFICATION

DiscoFuse: A Large-Scale Dataset for Discourse-Based Sentence Fusion

NAACL 2019 google-research-datasets/discofuse

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.

SENTENCE FUSION TEXT SIMPLIFICATION TRANSFER LEARNING

Learning How to Simplify From Explicit Labeling of Complex-Simplified Text Pairs

IJCNLP 2017 ghpaetzold/massalign

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