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        <title>Construction Grammar Provides Unique Insight into Neural Language Models</title>
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    <name type="personal">
        <namePart type="given">Leonie</namePart>
        <namePart type="family">Weissweiler</namePart>
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        <namePart type="given">Taiqi</namePart>
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    <name type="personal">
        <namePart type="given">Naoki</namePart>
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    <name type="personal">
        <namePart type="given">David</namePart>
        <namePart type="family">R. Mortensen</namePart>
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    <name type="personal">
        <namePart type="given">Lori</namePart>
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            <title>Proceedings of the First International Workshop on Construction Grammars and NLP (CxGs+NLP, GURT/SyntaxFest 2023)</title>
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            <namePart type="given">Claire</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Harish</namePart>
            <namePart type="family">Tayyar Madabushi</namePart>
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    <abstract>Construction Grammar (CxG) has recently been used as the basis for probing studies that have investigated the performance of large pretrained language models (PLMs) with respect to the structure and meaning of constructions. In this position paper, we make suggestions for the continuation and augmentation of this line of research. We look at probing methodology that was not designed with CxG in mind, as well as probing methodology that was designed for specific constructions. We analyse selected previous work in detail, and provide our view of the most important challenges and research questions that this promising new field faces.</abstract>
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        <url>https://aclanthology.org/2023.cxgsnlp-1.10</url>
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        <date>2023-03</date>
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            <start>85</start>
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%0 Conference Proceedings
%T Construction Grammar Provides Unique Insight into Neural Language Models
%A Weissweiler, Leonie
%A He, Taiqi
%A Otani, Naoki
%A R. Mortensen, David
%A Levin, Lori
%A Schütze, Hinrich
%Y Bonial, Claire
%Y Tayyar Madabushi, Harish
%S Proceedings of the First International Workshop on Construction Grammars and NLP (CxGs+NLP, GURT/SyntaxFest 2023)
%D 2023
%8 March
%I Association for Computational Linguistics
%C Washington, D.C.
%F weissweiler-etal-2023-construction
%X Construction Grammar (CxG) has recently been used as the basis for probing studies that have investigated the performance of large pretrained language models (PLMs) with respect to the structure and meaning of constructions. In this position paper, we make suggestions for the continuation and augmentation of this line of research. We look at probing methodology that was not designed with CxG in mind, as well as probing methodology that was designed for specific constructions. We analyse selected previous work in detail, and provide our view of the most important challenges and research questions that this promising new field faces.
%U https://aclanthology.org/2023.cxgsnlp-1.10
%P 85-95

Markdown (Informal)

[Construction Grammar Provides Unique Insight into Neural Language Models](https://aclanthology.org/2023.cxgsnlp-1.10) (Weissweiler et al., CxGsNLP-SyntaxFest 2023)

• Construction Grammar Provides Unique Insight into Neural Language Models (Weissweiler et al., CxGsNLP-SyntaxFest 2023)

ACL

• Leonie Weissweiler, Taiqi He, Naoki Otani, David R. Mortensen, Lori Levin, and Hinrich Schütze. 2023. Construction Grammar Provides Unique Insight into Neural Language Models. In Proceedings of the First International Workshop on Construction Grammars and NLP (CxGs+NLP, GURT/SyntaxFest 2023), pages 85–95, Washington, D.C.. Association for Computational Linguistics.