Fine-Tuned Llama for Multilingual Text-to-Text Coreference Resolution
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F26%3AXN3GBKKA" target="_blank" >RIV/00216208:11320/26:XN3GBKKA - isvavai.cz</a>
Result on the web
<a href="https://aclanthology.org/2025.crac-1.12/" target="_blank" >https://aclanthology.org/2025.crac-1.12/</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.18653/v1/2025.crac-1.12" target="_blank" >10.18653/v1/2025.crac-1.12</a>
Alternative languages
Result language
angličtina
Original language name
Fine-Tuned Llama for Multilingual Text-to-Text Coreference Resolution
Original language description
This paper describes our approach to the CRAC 2025 Shared Task on Multilingual Coreference Resolution. We compete in the LLM track, where the systems are limited to generative text-to-text approaches. Our system is based on Llama 3.1-8B, fine-tuned to tag the document with coreference annotations. We have made one significant modification to the text format provided by the organizers: The model relies on the syntactic head for mention span representation. Additionally, we use joint pre-training, and we train the model to generate empty nodes. We provide an in-depth analysis of the performance of our models, which reveals several implementation problems. Although our system ended up in last place, we achieved the best performance on 10 datasets out of 22 within the track. By fixing the discovered problems in the post-evaluation phase, we improved our results substantially, outperforming all the systems in the LLM track and even some unconstrained track systems.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
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Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the Eighth Workshop on Computational Models of Reference, Anaphora and Coreference
ISBN
979-8-89176-342-5
ISSN
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e-ISSN
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Number of pages
9
Pages from-to
140-148
Publisher name
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Place of publication
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Event location
Suzhou, China
Event date
Jan 1, 2026
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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