Since the late 1990s, automatic text simplification (ATS) was promoted as a natural
language processing (NLP) task with great potential to make texts more accessible to …

The success of a text simplification system heavily depends on the quality and quantity of
complex-simple sentence pairs in the training corpus, which are extracted by aligning …

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 …

In order to simplify a sentence, human editors perform multiple rewriting transformations:
they split it into several shorter sentences, paraphrase words (ie replacing complex words or …

Progress in sentence simplification has been hindered by a lack of labeled parallel
simplification data, particularly in languages other than English. We introduce MUSS, a …

Recent advancements in high-quality, large-scale English resources have pushed the
frontier of English Automatic Text Simplification (ATS) research. However, less work has …

Automatic text simplification systems help to reduce textual information barriers on the
internet. However, for languages other than English, only few parallel data to train these …

This work introduces a machine translation task where the output is aimed at audiences of
different levels of target language proficiency. We collect a high quality dataset of news …

Traditionally, Text Simplification is treated as a monolingual translation task where
sentences between source texts and their simplified counterparts are aligned for training …

Automatic text simplification can help patients to better understand their own clinical notes. A
major hurdle for the development of clinical text simplification methods is the lack of high …