Text simplification, defined narrowly, is the process of reducing the linguistic complexity of a
text, while still retaining the original information and meaning. More broadly, text …

The occurrence of unknown words in texts significantly hinders reading comprehension. To
improve accessibility for specific target populations, computational modeling has been …

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

Simple Wikipedia has dominated simplification research in the past 5 years. In this opinion
paper, we argue that focusing on Wikipedia limits simplification research. We back up our …

Automated simplification models aim to make input texts more readable. Such methods have
the potential to make complex information accessible to a wider audience, eg, providing …

Sentence Simplification (SS) aims to modify a sentence in order to make it easier to read
and understand. In order to do so, several rewriting transformations can be performed such …

Text simplification modifies syntax and lexicon to improve the understandability of language
for an end user. This survey identifies and classifies simplification research within the period …

Lexical simplification (LS) aims at replacing complex words with simpler alternatives. LS
commonly consists of three main steps: complex word identification, substitute generation …

Lexical Simplification is the task of replacing complex words with simpler alternatives. We
propose a novel, unsupervised approach for the task. It relies on two resources: a corpus of …

Edit-based approaches have recently shown promising results on multiple monolingual
sequence transduction tasks. In contrast to conventional sequence-to-sequence (Seq2Seq) …