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<pre>
Preface to the First Workshop on Current Trends in
Text Simplification
Horacio Saggion1 , Sanja Štajner2 , Daniel Ferrés1 and Kim Cheng Sheang1
1
    LaSTUS/TALN, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Spain
2
    Symanto Research, Germany



   Thanks to the availability of texts on the Web in recent years, increased knowledge and
information have been made available to broader audiences. However, the way in which a text is
written—vocabulary, syntax, text organisation/structure—can be difficult to read and understand
for many people, especially those with low literacy, cognitive or linguistic impairment, or those
with limited knowledge of the language of the text. Texts containing uncommon words or long
and complicated sentences can be difficult to read and understand by people as well as difficult
to analyse by machines. Automatic text simplification is the process of transforming a text into
another text which, ideally conveying the same message, will be easier to read and understand
by a broader audience.

   Research in text simplification has been approached from different angles: rule-based linguisti-
cally informed methods, unsupervised corpus-based techniques, supervised machine learning or
statistical machine translation have all been attempted in text simplification. Recently, research
in text simplification has, like in many other natural language processing areas, increased the
use of methods derived from the deep learning paradigm, and more specifically end-to-end
sequence to sequence, and transformer-based learning methods. In spite of the current advances
in the field, there are many important aspects of the simplification problem that need the
attention of our community, including but not limited to: the design of appropriate evaluation
metrics, the development of context-aware simplification solutions, the creation of appropriate
language resources to support research and evaluation, the deployment of simplification in real
environments for real users, the study of discourse factors in text simplification, the identifica-
tion of factors affecting the readability of a text, etc.

  In response to the call for papers for this workshop, we received seven submissions from
France, Germany, India, Poland, Spain and the United Kingdom. Each submission was rigorously
reviewed by three members of the Program Committee. The final program of the workshop
consists of six papers, which cover the topics of text simplification systems and evaluation
methods, and two invited talks.

  The workshop is co-located with the SEPLN 2021 conference and held on-line on 21st Septem-
ber 2021.
Proceedings of the First Workshop on Current Trends in Text Simplification (CTTS 2021), co-located with SEPLN 2021.
September 21st, 2021 (Online). Saggion, H., Štajner, S. and Ferrés, D. (Eds).
                                       © 2021 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
    CEUR
    Workshop
    Proceedings
                  http://ceur-ws.org
                  ISSN 1613-0073       CEUR Workshop Proceedings (CEUR-WS.org)
  We are grateful to Aline Villavicencio (University of Sheffield, UK) and Matt Huenerfauth
(Rochester Institute of Technology, USA) for accepting to give invited talks.

  We express our gratitude to the members of the program committee for their detailed reviews
and support.

  We acknowledge support from the project Context-aware Multilingual Text Simplification
(ConMuTeS) PID2019-109066GB-I00/AEI/10.13039/501100011033 awarded by Ministerio de
Ciencia, Innovación y Universidades (MCIU) and by Agencia Estatal de Investigación (AEI) of
Spain.


Workshop Organizers
Chairs
Horacio Saggion (Universitat Pompeu Fabra, Spain)
Sanja Štajner (Symanto Research, Germany)
Daniel Ferrés (Universitat Pompeu Fabra, Spain)


Proceedings
Kim Cheng Sheang (Universitat Pompeu Fabra, Spain)



Program Committee
Rodrigo Alarcón (Universidad Carlos III, Spain)
Sandra Aluísio (University of São Paulo, Brazil)
Fernando Alva Manchego (University of Sheffield, UK)
Susana Bautista (Universidad Francisco de Vitoria, Spain)
Antoine Bordes (Facebook, UK)
Stefan Bott (LoveToKnow Corp., Spain)
Remi Cardon (Université de Lille, France)
Eric De la Clergerie (INRIA, France)
Felice Dell’Orletta (Istituto di Linguistica Computazionale “Antonio Zampolli”, Italy)
Richard Evans (University of Wolverhampton, UK)
Thomas François (Université catholique de Louvain, Belgique)
Nuria Gala (Université Aix-Marseille, France)
Goran Glavaš (University of Mannheim, Germany)
Itziar Gonzalez-Dios (University of the Basque Country, Spain)
Natalia Grabar (Université de Lille, France)
Raquel Hervás (Universidad Complutense de Madrid, Spain)
David Kauchak (Pomona College, USA)
Elena Lloret (Universidad de Alicante, Spain)
Louis Martin (Facebook, UK)
Lourdes Moreno López (Universidad Carlos III, Spain)
Gustavo Henrique Paetzold (Universidade Tecnológica Federal do Paraná, Brazil)
Benoît Sagot (INRIA, France)
Carolina Scarton (University of Sheffield, UK)
Matthew Shardlow (Manchester Metropolitan University, UK)
Advaith Siddharthan (The Open University, UK)
Lucia Specia (Imperial College, UK)
Giulia Venturi (Istituto di Linguistica Computazionale “Antonio Zampolli”, Italy)
Victoria Yaneva (National Board of Medical Examiners, USA)

</pre>