GLaRef@ CRAC2025: Should we transform coreference resolution into a text generation task?

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F26%3AHK5PHB6V" target="_blank" >RIV/00216208:11320/26:HK5PHB6V - isvavai.cz</a>

Result on the web

<a href="https://aclanthology.org/2025.crac-1.10/" target="_blank" >https://aclanthology.org/2025.crac-1.10/</a>

DOI - Digital Object Identifier

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Result language

angličtina

Original language name

GLaRef@ CRAC2025: Should we transform coreference resolution into a text generation task?

Original language description

We present the submissions of our team to the Unconstrained and LLM tracks of the Computational Models of Reference, Anaphora and Coreference (CRAC2025) shared task, where we ended respectively in the fifth and the first place, but nevertheless with similar scores: average CoNLL-F1 scores of 61.57 and 62.96 on the test set, but with very large differences in computational cost. Indeed, the classical pair-wise resolution system submitted to the Unconstrained track obtained similar performance but with less than 10% of the computational cost. Reflecting on this fact, we point out problems that we ran into using generative AI to perform coreference resolution. We explain how the framework of text generation stands in the way of a reliable text-global coreference representation. Nonetheless, we realize there are many potential improvements of our LLM-system; we discuss them at the end of this article.

Czech name

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Czech description

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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)

Project

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Continuities

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Publication year

2025

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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

11

Pages from-to

119-129

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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