1 code implementation • 23 Nov 2022 • Mateus Karvat Camara, Adriana Postal, Tomas Henrique Maul, Gustavo Paetzold
Despite the great impact of lies in human societies and a meager 54% human accuracy for Deception Detection (DD), Machine Learning systems that perform automated DD are still not viable for proper application in real-life settings due to data scarcity.
no code implementations • WS 2018 • Gustavo Paetzold
We introduce the UTFPR system for the Implicit Emotions Shared Task of 2018: A compositional character-to-word recurrent neural network that does not exploit heavy and/or hard-to-obtain resources.
no code implementations • WS 2018 • Gustavo Paetzold
We present the UTFPR systems at the WMT 2018 parallel corpus filtering task.
no code implementations • COLING 2018 • Joachim Bingel, Gustavo Paetzold, Anders S{\o}gaard
Most previous research in text simplification has aimed to develop generic solutions, assuming very homogeneous target audiences with consistent intra-group simplification needs.
no code implementations • IJCNLP 2017 • Gustavo Paetzold, Fern Alva-Manchego, o, Lucia Specia
We introduce MASSAlign: a Python library for the alignment and annotation of monolingual comparable documents.
1 code implementation • IJCNLP 2017 • Fern Alva-Manchego, o, Joachim Bingel, Gustavo Paetzold, Carolina Scarton, Lucia Specia
Current research in text simplification has been hampered by two central problems: (i) the small amount of high-quality parallel simplification data available, and (ii) the lack of explicit annotations of simplification operations, such as deletions or substitutions, on existing data.
Ranked #8 on
Text Simplification
on PWKP / WikiSmall
(SARI metric)
no code implementations • IJCNLP 2017 • Gustavo Paetzold, Lucia Specia
There is no question that our research community have, and still has been producing an insurmountable amount of interesting strategies, models and tools to a wide array of problems and challenges in diverse areas of knowledge.
no code implementations • WS 2017 • Marcos Zampieri, Shervin Malmasi, Gustavo Paetzold, Lucia Specia
This paper revisits the problem of complex word identification (CWI) following up the SemEval CWI shared task.
no code implementations • EACL 2017 • Gustavo Paetzold, Lucia Specia
We present a new Lexical Simplification approach that exploits Neural Networks to learn substitutions from the Newsela corpus - a large set of professionally produced simplifications.
no code implementations • COLING 2016 • Gustavo Paetzold, Lucia Specia
We introduce Anita: a flexible and intelligent Text Adaptation tool for web content that provides Text Simplification and Text Enhancement modules.
no code implementations • COLING 2016 • Gustavo Paetzold, Lucia Specia
We report three user studies in which the Lexical Simplification needs of non-native English speakers are investigated.
no code implementations • COLING 2016 • Carolina Scarton, Gustavo Paetzold, Lucia Specia
The goal of QE is to estimate the quality of language output applications without the need of human references.
no code implementations • COLING 2016 • Gustavo Paetzold, Lucia Specia
Exploring language usage through frequency analysis in large corpora is a defining feature in most recent work in corpus and computational linguistics.
no code implementations • LREC 2016 • Gustavo Paetzold, Lucia Specia
Lexical Simplification is the task of replacing complex words in a text with simpler alternatives.