SARI
Related Papers
EditNTS: An Neural Programmer-Interpreter Model for Sentence Simplification through Explicit Editing
AbstractWe present the first sentence simplification model that learns explicit edit operations (ADD, DELETE, and KEEP) via a neural programmer-interpreter approach. Most current neural sentence simplification systems are variants of …...
Generating Animations from Screenplays
AbstractAutomatically generating animation from natural language text finds application in a number of areas e.g. movie script writing, instructional videos, and public safety. However, translating natural language text into animation …...
On the Helpfulness of Document Context to Sentence Simplification
AbstractMost of the research on text simplification is limited to sentence level nowadays. In this paper, we are the first to investigate the helpfulness of document context on sentence simplification …...
SimplifyUR: Unsupervised Lexical Text Simplification for Urdu
AbstractThis paper presents the first attempt at Automatic Text Simplification (ATS) for Urdu, the language of 170 million people worldwide. Being a low-resource language in terms of standard linguistic resources, …...
Investigating Text Simplification Evaluation
Modern text simplification (TS) heavily relies on the availability of gold standard data to build machine learning models. However, ex- isting studies show that parallel TS corpora contain inaccurate simplifications …...
Keep It Simple: Unsupervised Simplification of Multi-Paragraph Text
AbstractThis work presents Keep it Simple (KiS), a new approach to unsupervised text simplification which learns to balance a reward across three properties: fluency, salience and simplicity. We train the …...
Linguistic Corpus Annotation for Automatic Text Simplification Evaluation
AbstractEvaluating automatic text simplification (ATS) systems is a difficult task that is either performed by automatic metrics or user-based evaluations. However, from a linguistic point-of-view, it is not always clear …...
Multitasking Framework for Unsupervised Simple Definition Generation
AbstractThe definition generation task can help language learners by providing explanations for unfamiliar words. This task has attracted much attention in recent years. We propose a novel task of Simple …...
NapSS: Paragraph-level Medical Text Simplification via Narrative Prompting and Sentence-matching Summarization
AbstractAccessing medical literature is difficult for laypeople as the content is written for specialists and contains medical jargon. Automated text simplification methods offer a potential means to address this issue. …...
SIMSUM: Document-level Text Simplification via Simultaneous Summarization
AbstractDocument-level text simplification is a specific type of simplification which involves simplifying documents consisting of several sentences by rewriting them into fewer or more sentences. In this paper, we propose …...