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| Main Authors: | , , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2509.17796 |
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| _version_ | 1866908632220696576 |
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| author | Novák, Michal Konopík, Miloslav Nedoluzhko, Anna Popel, Martin Pražák, Ondřej Sido, Jakub Straka, Milan Žabokrtský, Zdeněk Zeman, Daniel |
| author_facet | Novák, Michal Konopík, Miloslav Nedoluzhko, Anna Popel, Martin Pražák, Ondřej Sido, Jakub Straka, Milan Žabokrtský, Zdeněk Zeman, Daniel |
| contents | The paper presents an overview of the fourth edition of the Shared Task on Multilingual Coreference Resolution, organized as part of the CODI-CRAC 2025 workshop. As in the previous editions, participants were challenged to develop systems that identify mentions and cluster them according to identity coreference.
A key innovation of this year's task was the introduction of a dedicated Large Language Model (LLM) track, featuring a simplified plaintext format designed to be more suitable for LLMs than the original CoNLL-U representation.
The task also expanded its coverage with three new datasets in two additional languages, using version 1.3 of CorefUD - a harmonized multilingual collection of 22 datasets in 17 languages.
In total, nine systems participated, including four LLM-based approaches (two fine-tuned and two using few-shot adaptation). While traditional systems still kept the lead, LLMs showed clear potential, suggesting they may soon challenge established approaches in future editions. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_17796 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Findings of the Fourth Shared Task on Multilingual Coreference Resolution: Can LLMs Dethrone Traditional Approaches? Novák, Michal Konopík, Miloslav Nedoluzhko, Anna Popel, Martin Pražák, Ondřej Sido, Jakub Straka, Milan Žabokrtský, Zdeněk Zeman, Daniel Computation and Language The paper presents an overview of the fourth edition of the Shared Task on Multilingual Coreference Resolution, organized as part of the CODI-CRAC 2025 workshop. As in the previous editions, participants were challenged to develop systems that identify mentions and cluster them according to identity coreference. A key innovation of this year's task was the introduction of a dedicated Large Language Model (LLM) track, featuring a simplified plaintext format designed to be more suitable for LLMs than the original CoNLL-U representation. The task also expanded its coverage with three new datasets in two additional languages, using version 1.3 of CorefUD - a harmonized multilingual collection of 22 datasets in 17 languages. In total, nine systems participated, including four LLM-based approaches (two fine-tuned and two using few-shot adaptation). While traditional systems still kept the lead, LLMs showed clear potential, suggesting they may soon challenge established approaches in future editions. |
| title | Findings of the Fourth Shared Task on Multilingual Coreference Resolution: Can LLMs Dethrone Traditional Approaches? |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2509.17796 |