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        <title>LeSS: A Computationally-Light Lexical Simplifier for Spanish</title>
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        <namePart type="given">Sanja</namePart>
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    <name type="personal">
        <namePart type="given">Daniel</namePart>
        <namePart type="family">Ibanez</namePart>
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    <name type="personal">
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            <title>Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing</title>
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            <namePart type="given">Ruslan</namePart>
            <namePart type="family">Mitkov</namePart>
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        <name type="personal">
            <namePart type="given">Galia</namePart>
            <namePart type="family">Angelova</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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            <publisher>INCOMA Ltd., Shoumen, Bulgaria</publisher>
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    <abstract>Due to having knowledge of only basic vocabulary, many people cannot understand up-to-date written information and thus make informed decisions and fully participate in the society. We propose LeSS, a modular lexical simplification architecture that outperforms state-of-the-art lexical simplification systems for Spanish. In addition to its state-of-the-art performance, LeSS is computationally light, using much less disk space, CPU and GPU, and having faster loading and execution time than the transformer-based lexical simplification models which are predominant in the field.</abstract>
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        <url>https://aclanthology.org/2023.ranlp-1.120</url>
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        <date>2023-09</date>
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            <start>1132</start>
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%0 Conference Proceedings
%T LeSS: A Computationally-Light Lexical Simplifier for Spanish
%A Stajner, Sanja
%A Ibanez, Daniel
%A Saggion, Horacio
%Y Mitkov, Ruslan
%Y Angelova, Galia
%S Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing
%D 2023
%8 September
%I INCOMA Ltd., Shoumen, Bulgaria
%C Varna, Bulgaria
%F stajner-etal-2023-less
%X Due to having knowledge of only basic vocabulary, many people cannot understand up-to-date written information and thus make informed decisions and fully participate in the society. We propose LeSS, a modular lexical simplification architecture that outperforms state-of-the-art lexical simplification systems for Spanish. In addition to its state-of-the-art performance, LeSS is computationally light, using much less disk space, CPU and GPU, and having faster loading and execution time than the transformer-based lexical simplification models which are predominant in the field.
%U https://aclanthology.org/2023.ranlp-1.120
%P 1132-1142

Markdown (Informal)

[LeSS: A Computationally-Light Lexical Simplifier for Spanish](https://aclanthology.org/2023.ranlp-1.120) (Stajner et al., RANLP 2023)

• LeSS: A Computationally-Light Lexical Simplifier for Spanish (Stajner et al., RANLP 2023)

ACL

• Sanja Stajner, Daniel Ibanez, and Horacio Saggion. 2023. LeSS: A Computationally-Light Lexical Simplifier for Spanish. In Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing, pages 1132–1142, Varna, Bulgaria. INCOMA Ltd., Shoumen, Bulgaria.