Survey of the state of the art in natural language generation: Core tasks, applications and evaluation

A Gatt, E Krahmer - Journal of Artificial Intelligence Research, 2018 - jair.org
This paper surveys the current state of the art in Natural Language Generation (NLG),
defined as the task of generating text or speech from non-linguistic input. A survey of NLG is …

Automated text simplification: a survey

SS Al-Thanyyan, AM Azmi - ACM Computing Surveys (CSUR), 2021 - dl.acm.org
Text simplification (TS) reduces the complexity of the text to improve its readability and
understandability, while possibly retaining its original information content. Over time, TS has …

[PDF][PDF] Abstractive sentence summarization with attentive recurrent neural networks

S Chopra, M Auli, AM Rush - … of the 2016 conference of the North …, 2016 - aclanthology.org
Abstract Abstractive Sentence Summarization generates a shorter version of a given
sentence while attempting to preserve its meaning. We introduce a conditional recurrent …

Dear sir or madam, may I introduce the GYAFC dataset: Corpus, benchmarks and metrics for formality style transfer

S Rao, J Tetreault - arXiv preprint arXiv:1803.06535, 2018 - arxiv.org
Style transfer is the task of automatically transforming a piece of text in one particular style
into another. A major barrier to progress in this field has been a lack of training and …

Sentence simplification with deep reinforcement learning

X Zhang, M Lapata - arXiv preprint arXiv:1703.10931, 2017 - arxiv.org
Sentence simplification aims to make sentences easier to read and understand. Most recent
approaches draw on insights from machine translation to learn simplification rewrites from …

Optimizing statistical machine translation for text simplification

W Xu, C Napoles, E Pavlick, Q Chen… - Transactions of the …, 2016 - direct.mit.edu
Most recent sentence simplification systems use basic machine translation models to learn
lexical and syntactic paraphrases from a manually simplified parallel corpus. These methods …

Deep learning for joint source-channel coding of text

N Farsad, M Rao, A Goldsmith - 2018 IEEE international …, 2018 - ieeexplore.ieee.org
We consider the problem of joint source and channel coding of structured data such as
natural language over a noisy channel. The typical approach to this problem in both theory …

Problems in current text simplification research: New data can help

W Xu, C Callison-Burch, C Napoles - Transactions of the Association …, 2015 - direct.mit.edu
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 …

Exploring neural text simplification models

S Nisioi, S Štajner, SP Ponzetto… - Proceedings of the 55th …, 2017 - aclanthology.org
We present the first attempt at using sequence to sequence neural networks to model text
simplification (TS). Unlike the previously proposed automated TS systems, our neural text …

Controllable sentence simplification

L Martin, B Sagot, E de la Clergerie… - arXiv preprint arXiv …, 2019 - arxiv.org
Text simplification aims at making a text easier to read and understand by simplifying
grammar and structure while keeping the underlying information identical. It is often …