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    <titleInfo>
        <title>Exploring Language Representation through a Resource Inventory Project</title>
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    <name type="personal">
        <namePart type="given">Carolyn</namePart>
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            <title>Proceedings of the Sixth Workshop on Teaching NLP</title>
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        <name type="personal">
            <namePart type="given">Sana</namePart>
            <namePart type="family">Al-azzawi</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Laura</namePart>
            <namePart type="family">Biester</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">György</namePart>
            <namePart type="family">Kovács</namePart>
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        <name type="personal">
            <namePart type="given">Ana</namePart>
            <namePart type="family">Marasović</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Leena</namePart>
            <namePart type="family">Mathur</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Margot</namePart>
            <namePart type="family">Mieskes</namePart>
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        <name type="personal">
            <namePart type="given">Leonie</namePart>
            <namePart type="family">Weissweiler</namePart>
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    <abstract>The increasing scale of large language models has led some students to wonder what contributions can be made in academia. However, students are often unaware that LLM-based approaches are not feasible for the majority of the world’s languages due to lack of data availability. This paper presents a research project in which students explore the issue of language representation by creating an inventory of the data, preprocessing, and model resources available for a less-resourced language. Students are put into small groups and assigned a language to research. Within the group, students take on one of three roles: dataset investigator, preprocessing investigator, or downstream task investigator. Students then work together to create a 7-page research report about their language.</abstract>
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        <date>2024-08</date>
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            <start>91</start>
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%0 Conference Proceedings
%T Exploring Language Representation through a Resource Inventory Project
%A Anderson, Carolyn
%Y Al-azzawi, Sana
%Y Biester, Laura
%Y Kovács, György
%Y Marasović, Ana
%Y Mathur, Leena
%Y Mieskes, Margot
%Y Weissweiler, Leonie
%S Proceedings of the Sixth Workshop on Teaching NLP
%D 2024
%8 August
%I Association for Computational Linguistics
%C Bangkok, Thailand
%F anderson-2024-exploring-language
%X The increasing scale of large language models has led some students to wonder what contributions can be made in academia. However, students are often unaware that LLM-based approaches are not feasible for the majority of the world’s languages due to lack of data availability. This paper presents a research project in which students explore the issue of language representation by creating an inventory of the data, preprocessing, and model resources available for a less-resourced language. Students are put into small groups and assigned a language to research. Within the group, students take on one of three roles: dataset investigator, preprocessing investigator, or downstream task investigator. Students then work together to create a 7-page research report about their language.
%U https://aclanthology.org/2024.teachingnlp-1.14
%P 91-93

Markdown (Informal)

[Exploring Language Representation through a Resource Inventory Project](https://aclanthology.org/2024.teachingnlp-1.14) (Anderson, TeachingNLP-WS 2024)

• Exploring Language Representation through a Resource Inventory Project (Anderson, TeachingNLP-WS 2024)

ACL

• Carolyn Anderson. 2024. Exploring Language Representation through a Resource Inventory Project. In Proceedings of the Sixth Workshop on Teaching NLP, pages 91–93, Bangkok, Thailand. Association for Computational Linguistics.