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    <journal-meta />
    <article-meta>
      <title-group>
        <article-title>CEUR Workshop Proceedings</article-title>
      </title-group>
      <contrib-group>
        <aff id="aff0">
          <label>0</label>
          <institution>An Approach to a Cost-Effective and Controllable Text Generation Architecture Iván Martínez-Murillo .</institution>
          <addr-line>..................................................................................................1-8</addr-line>
        </aff>
      </contrib-group>
      <fpage>60</fpage>
      <lpage>68</lpage>
    </article-meta>
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  <body>
    <sec id="sec-1">
      <title>Papers</title>
      <sec id="sec-1-1">
        <title>Improving AutoML for LLMs via Knowledge-Based Meta-Learning</title>
        <p>Ernesto Luis Estevanell-Valladares..………...………...……………………….…….…….….....….69-77</p>
      </sec>
      <sec id="sec-1-2">
        <title>Evaluation of Large Language Models in Multilingual Settings</title>
        <p>Maite Heredia Arribas…………...…………………………………….…………………….…..….....87-95
Can Natural Language Processing Technologies Help the Digital Transformation of Local Public</p>
      </sec>
      <sec id="sec-1-3">
        <title>Administrations?</title>
        <p>Ángel Lloret …………………...….……………………………….…………………….…….….....105-113</p>
      </sec>
      <sec id="sec-1-4">
        <title>Using Argumentation Theory to Fight Misinformation</title>
        <p>Blanca Calvo Figueras……….……………….…………………….……....................................114-122</p>
      </sec>
      <sec id="sec-1-5">
        <title>Multimodal Emotion Recognition in the Political Domain in Spanish</title>
        <p>Ronghao Pan………………………….……….…………………….……....................................123-131</p>
      </sec>
      <sec id="sec-1-6">
        <title>Analysis of Lexical Ambiguity in Vector Space Models</title>
        <p>Marta Vázquez Abuín……….………………….…………….…….…….....................................132-139
Leveraging Temporal Analysis to Predict the Impact of Political Messages on Social Media in</p>
      </sec>
      <sec id="sec-1-7">
        <title>Spanish</title>
      </sec>
      <sec id="sec-1-8">
        <title>Enhancing Trustworthy in NLP Systems Through Explainability</title>
        <p>Santiago González-Silot……………………….…………………….……...................................149-155
Adaptation of Large Language Models for Spanish Text Generation in Responsible AI Problems</p>
        <p>María Estrella Vallecillo Rodríguez..………….…………………….……...................................156-163</p>
      </sec>
      <sec id="sec-1-9">
        <title>Word Sense Disambiguation for Linking Domain-Specific Resources</title>
        <p>Lucía Palacios.………………………………….…………………….……...................................164-172</p>
      </sec>
      <sec id="sec-1-10">
        <title>Separating Linguistic Competence from Factual Knowledge in Large Language Models</title>
        <p>Jaime Collado-Montañez...………………….…………………….……......................................173-177</p>
      </sec>
      <sec id="sec-1-11">
        <title>Automatic Text Classification using Readability Levels in Galician and Spanish</title>
        <p>Sandra Rodríguez Rey…...………………….…………………….…….....................................193-201
Proceedings of the Doctoral Symposium on Natural Language Processing 2024
(NLP-DS-2024)</p>
      </sec>
    </sec>
    <sec id="sec-2">
      <title>Organization</title>
      <sec id="sec-2-1">
        <title>Organizing committee</title>
        <p>Alba Bonet Jover
David Vilares Calvo
Elena Lloret Pastor
M. Dolores Molina González
Salud María Jiménez Zafra</p>
        <p>Universidad de Alicante</p>
        <p>alba.bonet@dlsi.ua.es
Universidad de Alicante</p>
        <p>elloret@dlsi.ua.es
Universidad de Jaén</p>
        <p>mdmolina@ujaen.es
Universidad de Jaén
sjzafra@ujaen.es
Edited in: Universidad de Jaén, Universidad de Alicante and Universidad de A Coruña
Year: 2024</p>
      </sec>
      <sec id="sec-2-2">
        <title>Editors</title>
        <p>Alba Bonet Jover
David Vilares Calvo
Elena Lloret Pastor
Universidad de Alicante
alba.bonet@dlsi.ua.es
Universidad de A Coruña
david.vilares@udc.es
Universidad de Alicante
elloret@dlsi.ua.es
M. Dolores Molina González
Salud María Jiménez Zafra
Universidad de Jaén
Universidad de Jaén
Published by: CEUR Workshop Proceedings</p>
      </sec>
      <sec id="sec-2-3">
        <title>Program Committee</title>
        <p>These proceedings have been partially supported by projects with reference 2022/TL22/00215337,
2022/TL22/00215336, 2022/TL22/00215335 and 2022/TL22/00215334 funded by Ministerio de Asuntos
Económicos y Transformación Digital and Plan de Recuperación, Transformación y Resiliencia - Funded by
the European Union - NextGenerationEU; and Cátedra HiTZ de Inteligencia Artificial y Tecnología de la
Lengua (TSI100923-2023-1) supported by Plan de Recuperación, Transformación y Resiliencia - Funded
by the European Union, as well as the Secretaría de Estado de Telecomunicaciones e Infraestructuras
Digitales.
Proceedings of the Doctoral Symposium on Natural Language Processing 2024
(NLP-DS-2024)</p>
      </sec>
    </sec>
    <sec id="sec-3">
      <title>Preamble</title>
      <p>The Spanish Society for Natural Language Processing has organized the 7th edition of the Doctoral
Symposium on Natural Language Processing held in Valladolid on September 26, 2024 as part of the XL
International Conference of the Spanish Society for Natural Language Processing (SEPLN 2024).
The aim of the Doctoral Symposium is to promote scientific vocations in the field of Language Technologies
and Natural Language Processing (NLP). To this end, it organizes a meeting point where PhD students in
the area of NLP can present their work. Moreover, they receive constructive feedback and guidance from
experienced researchers in their area of work.</p>
      <p>In the 2024 edition, 24 PhD students participated. All participants submitted a paper describing their
proposals, all of them being accepted after review by two members of the program committee and by the
organizing committee.
The editors</p>
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  <back>
    <ref-list>
      <ref id="ref1">
        <mixed-citation>
          <article-title>Copyright @ 2024 for the individual papers by the papers' authors.</article-title>
        </mixed-citation>
      </ref>
      <ref id="ref2">
        <mixed-citation>
          <article-title>Copyright @ 2024 for the volume as a collection by its editors. This volume and its papers are published under the Creative Commons License Attribution 4.0 International (CC BY4.0).</article-title>
        </mixed-citation>
      </ref>
    </ref-list>
  </back>
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