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    <titleInfo>
        <title>Monolingual text summarization for Indic Languages using LLMs</title>
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    <name type="personal">
        <namePart type="given">Jothir</namePart>
        <namePart type="given">Adithya</namePart>
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        <namePart type="given">Nithish</namePart>
        <namePart type="given">Kumar</namePart>
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    <name type="personal">
        <namePart type="given">Felicia</namePart>
        <namePart type="given">Lilian</namePart>
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    <name type="personal">
        <namePart type="given">Mahalakshmi</namePart>
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            <title>Proceedings of the 21st International Conference on Natural Language Processing (ICON)</title>
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            <namePart type="given">Sobha</namePart>
            <namePart type="family">Lalitha Devi</namePart>
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    <abstract>We have analyzed the growth of advanced text summarization method leveraging LLM for Indic language. Text summarization involves transforming a longer text information into a more concise version, ensuring that the most prominent information and key meanings are maintained. Our goal is to produce concise and accurate summaries from longer texts, focusing on maintaining detailed information and coherence. We utilize NLP techniques for text cleaning, keyword extraction and summarization, along with performance evaluation metrics such as ROUGE score, BLEU score and BERT Score. The results demonstrate an incremental improvement in the quality of generated summaries, with a particular emphasis on enhancing informativeness while minimizing redundancy. This research work also highlights the importance of tuning parameters and leveraging advanced models for producing high quality summaries in diverse domains for Indic Language.</abstract>
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        <url>https://aclanthology.org/2024.icon-1.11/</url>
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%0 Conference Proceedings
%T Monolingual text summarization for Indic Languages using LLMs
%A T K, Jothir Adithya
%A S, Nithish Kumar
%A J, Felicia Lilian
%A S, Mahalakshmi
%Y Lalitha Devi, Sobha
%Y Arora, Karunesh
%S Proceedings of the 21st International Conference on Natural Language Processing (ICON)
%D 2024
%8 December
%I NLP Association of India (NLPAI)
%C AU-KBC Research Centre, Chennai, India
%F t-k-etal-2024-monolingual
%X We have analyzed the growth of advanced text summarization method leveraging LLM for Indic language. Text summarization involves transforming a longer text information into a more concise version, ensuring that the most prominent information and key meanings are maintained. Our goal is to produce concise and accurate summaries from longer texts, focusing on maintaining detailed information and coherence. We utilize NLP techniques for text cleaning, keyword extraction and summarization, along with performance evaluation metrics such as ROUGE score, BLEU score and BERT Score. The results demonstrate an incremental improvement in the quality of generated summaries, with a particular emphasis on enhancing informativeness while minimizing redundancy. This research work also highlights the importance of tuning parameters and leveraging advanced models for producing high quality summaries in diverse domains for Indic Language.
%U https://aclanthology.org/2024.icon-1.11/
%P 94-101

Markdown (Informal)

[Monolingual text summarization for Indic Languages using LLMs](https://aclanthology.org/2024.icon-1.11/) (T K et al., ICON 2024)

• Monolingual text summarization for Indic Languages using LLMs (T K et al., ICON 2024)

ACL

• Jothir Adithya T K, Nithish Kumar S, Felicia Lilian J, and Mahalakshmi S. 2024. Monolingual text summarization for Indic Languages using LLMs. In Proceedings of the 21st International Conference on Natural Language Processing (ICON), pages 94–101, AU-KBC Research Centre, Chennai, India. NLP Association of India (NLPAI).