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) …

This paper outlines the ethical implications of text simplification within the framework of
assistive systems. We argue that a distinction should be made between the technologies …

Lexical Simplification is the process of replacing complex words in a given sentence with
simpler alternatives of equivalent meaning. This task has wide applicability both as an …

Abstract We release the Simple Paraphrase Database, a subset of of the Paraphrase
Database (PPDB) adapted for the task of text simplification. We train a supervised model to …

Lexical Simplification is the task of replacing complex words in a text with simpler
alternatives. A variety of strategies have been devised for this challenge, yet there has been …

We introduce a bootstrapping algorithm for regression that exploits word embedding
models. We use it to infer four psycholinguistic properties of words: Familiarity, Age of …

Text simplification reduces the language complexity of professional content for accessibility
purposes. End-to-end neural network models have been widely adopted to directly generate …

We introduce the SV000gg systems: two Ensemble Methods for the Complex Word
Identification task of SemEval 2016. While the SV000gg-Hard system exploits basic Hard …

We have constructed the simplified corpus for the Japanese language and selected the core
vocabulary. The corpus has 50,000 manually simplified and aligned sentences. This corpus …