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        <namePart type="given">Sobha</namePart>
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        <namePart type="given">Pattabhi</namePart>
        <namePart type="family">Rk Rao</namePart>
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            <title>Proceedings of the 4th Shared Task on Discourse Relation Parsing and Treebanking (DISRPT 2025)</title>
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            <namePart type="given">Yang</namePart>
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    <abstract>The work presented here describes our participation in DISRPT 2025 shared task in three tasks, Task1: Discourse Unit Segmentation across Formalisms, Task 2: Discourse Connective Identification across Languages and Task 3: Discourse Relation Classification across Formalisms. We have fine-tuned XLM-RoBERTa, a language model to address these three tasks. We have come up with one single multilingual language model for each task. Our system handles data in both the formats .conllu and .tok and different discourse formalisms. We have obtained encouraging results. The performance on test data in the three tasks is similar to the results obtained for the development data.</abstract>
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%0 Conference Proceedings
%T SeCoRel: Multilingual Discourse Analysis in DISRPT 2025
%A Lalitha Devi, Sobha
%A Rk Rao, Pattabhi
%A Sundar Ram, Vijay
%Y Braud, Chloé
%Y Liu, Yang Janet
%Y Muller, Philippe
%Y Zeldes, Amir
%Y Li, Chuyuan
%S Proceedings of the 4th Shared Task on Discourse Relation Parsing and Treebanking (DISRPT 2025)
%D 2025
%8 November
%I Association for Computational Linguistics
%C Suzhou, China
%@ 979-8-89176-344-9
%F lalitha-devi-etal-2025-secorel
%X The work presented here describes our participation in DISRPT 2025 shared task in three tasks, Task1: Discourse Unit Segmentation across Formalisms, Task 2: Discourse Connective Identification across Languages and Task 3: Discourse Relation Classification across Formalisms. We have fine-tuned XLM-RoBERTa, a language model to address these three tasks. We have come up with one single multilingual language model for each task. Our system handles data in both the formats .conllu and .tok and different discourse formalisms. We have obtained encouraging results. The performance on test data in the three tasks is similar to the results obtained for the development data.
%U https://aclanthology.org/2025.disrpt-1.6/
%P 79-86

Markdown (Informal)

[SeCoRel: Multilingual Discourse Analysis in DISRPT 2025](https://aclanthology.org/2025.disrpt-1.6/) (Lalitha Devi et al., DISRPT 2025)

• SeCoRel: Multilingual Discourse Analysis in DISRPT 2025 (Lalitha Devi et al., DISRPT 2025)

ACL

• Sobha Lalitha Devi, Pattabhi Rk Rao, and Vijay Sundar Ram. 2025. SeCoRel: Multilingual Discourse Analysis in DISRPT 2025. In Proceedings of the 4th Shared Task on Discourse Relation Parsing and Treebanking (DISRPT 2025), pages 79–86, Suzhou, China. Association for Computational Linguistics.