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    <titleInfo>
        <title>Citation-Based Summarization of Landmark Judgments</title>
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        <namePart type="family">Bindal</namePart>
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    <name type="personal">
        <namePart type="given">Vikas</namePart>
        <namePart type="family">Kumar</namePart>
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    <name type="personal">
        <namePart type="given">Vasudha</namePart>
        <namePart type="family">Bhatnagar</namePart>
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    <name type="personal">
        <namePart type="given">Parikshet</namePart>
        <namePart type="family">Sirohi</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
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    <name type="personal">
        <namePart type="given">Ashwini</namePart>
        <namePart type="family">Siwal</namePart>
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        <dateIssued>2023-12</dateIssued>
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            <title>Proceedings of the 20th International Conference on Natural Language Processing (ICON)</title>
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        <name type="personal">
            <namePart type="given">Jyoti</namePart>
            <namePart type="family">D. Pawar</namePart>
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        <name type="personal">
            <namePart type="given">Sobha</namePart>
            <namePart type="family">Lalitha Devi</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <originInfo>
            <publisher>NLP Association of India (NLPAI)</publisher>
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    <abstract>Landmark judgments are of prime importance in the Common Law System because of their exceptional jurisprudence and frequent references in other judgments. In this work, we leverage contextual references available in citing judgments to create an extractive summary of the target judgment. We evaluate the proposed algorithm on two datasets curated from the judgments of Indian Courts and find the results promising.</abstract>
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        <url>https://aclanthology.org/2023.icon-1.56</url>
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        <date>2023-12</date>
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            <start>588</start>
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%0 Conference Proceedings
%T Citation-Based Summarization of Landmark Judgments
%A Bindal, Purnima
%A Kumar, Vikas
%A Bhatnagar, Vasudha
%A Sirohi, Parikshet
%A Siwal, Ashwini
%Y D. Pawar, Jyoti
%Y Lalitha Devi, Sobha
%S Proceedings of the 20th International Conference on Natural Language Processing (ICON)
%D 2023
%8 December
%I NLP Association of India (NLPAI)
%C Goa University, Goa, India
%F purnima-etal-2023-citation
%X Landmark judgments are of prime importance in the Common Law System because of their exceptional jurisprudence and frequent references in other judgments. In this work, we leverage contextual references available in citing judgments to create an extractive summary of the target judgment. We evaluate the proposed algorithm on two datasets curated from the judgments of Indian Courts and find the results promising.
%U https://aclanthology.org/2023.icon-1.56
%P 588-593

Markdown (Informal)

[Citation-Based Summarization of Landmark Judgments](https://aclanthology.org/2023.icon-1.56) (Bindal et al., ICON 2023)

• Citation-Based Summarization of Landmark Judgments (Bindal et al., ICON 2023)

ACL

• Purnima Bindal, Vikas Kumar, Vasudha Bhatnagar, Parikshet Sirohi, and Ashwini Siwal. 2023. Citation-Based Summarization of Landmark Judgments. In Proceedings of the 20th International Conference on Natural Language Processing (ICON), pages 588–593, Goa University, Goa, India. NLP Association of India (NLPAI).