@inproceedings{shardlow-etal-2024-extensible,
    title = "An Extensible Massively Multilingual Lexical Simplification Pipeline Dataset using the {M}ulti{LS} Framework",
    author = {Shardlow, Matthew  and
      Alva-Manchego, Fernando  and
      Batista-Navarro, Riza  and
      Bott, Stefan  and
      Calderon Ramirez, Saul  and
      Cardon, R{\'e}mi  and
      Fran{\c{c}}ois, Thomas  and
      Hayakawa, Akio  and
      Horbach, Andrea  and
      H{\"u}lsing, Anna  and
      Ide, Yusuke  and
      Imperial, Joseph Marvin  and
      Nohejl, Adam  and
      North, Kai  and
      Occhipinti, Laura  and
      Per{\'e}z Rojas, Nelson  and
      Raihan, Nishat  and
      Ranasinghe, Tharindu  and
      Solis Salazar, Martin  and
      Zampieri, Marcos  and
      Saggion, Horacio},
    editor = "Wilkens, Rodrigo  and
      Cardon, R{\'e}mi  and
      Todirascu, Amalia  and
      Gala, N{\'u}ria",
    booktitle = "Proceedings of the 3rd Workshop on Tools and Resources for People with REAding DIfficulties (READI) @ LREC-COLING 2024",
    month = may,
    year = "2024",
    address = "Torino, Italia",
    publisher = "ELRA and ICCL",
    url = "https://aclanthology.org/2024.readi-1.4",
    pages = "38--46",
    abstract = "We present preliminary findings on the MultiLS dataset, developed in support of the 2024 Multilingual Lexical Simplification Pipeline (MLSP) Shared Task. This dataset currently comprises of 300 instances of lexical complexity prediction and lexical simplification across 10 languages. In this paper, we (1) describe the annotation protocol in support of the contribution of future datasets and (2) present summary statistics on the existing data that we have gathered. Multilingual lexical simplification can be used to support low-ability readers to engage with otherwise difficult texts in their native, often low-resourced, languages.",
}

We present preliminary findings on the MultiLS dataset, developed in support of the 2024 Multilingual Lexical Simplification Pipeline (MLSP) Shared Task. This dataset currently comprises of 300 instances of lexical complexity prediction and lexical simplification across 10 languages. In this paper, we (1) describe the annotation protocol in support of the contribution of future datasets and (2) present summary statistics on the existing data that we have gathered. Multilingual lexical simplification can be used to support low-ability readers to engage with otherwise difficult texts in their native, often low-resourced, languages.
Shardlow, Matthew Alva-Manchego, Fern o Batista-Navarro, Riza Bott, Stefan Calderon Ramirez, Saul Cardon, R{\'e}mi Fran{\c{c}}ois, Thomas Hayakawa, Akio Horbach, Andrea H{\"u}lsing, Anna Ide, Yusuke Imperial, Joseph Marvin Nohejl, Adam North, Kai Occhipinti, Laura Per{\'e}z Rojas, Nelson Raihan, Nishat Ranasinghe, Tharindu Solis Salazar, Martin Zampieri, Marcos Saggion, Horacio
An Extensible Massively Multilingual Lexical Simplification Pipeline Dataset using the MultiLS Framework