@inproceedings{scherrer-etal-2025-findings,
title = "Findings of the {V}ar{D}ial Evaluation Campaign 2025: The {N}or{SID} Shared Task on {N}orwegian Slot, Intent and Dialect Identification",
author = "Scherrer, Yves and
van der Goot, Rob and
M{\ae}hlum, Petter",
editor = "Scherrer, Yves and
Jauhiainen, Tommi and
Ljube{\v{s}}i{\'c}, Nikola and
Nakov, Preslav and
Tiedemann, Jorg and
Zampieri, Marcos",
booktitle = "Proceedings of the 12th Workshop on NLP for Similar Languages, Varieties and Dialects",
month = jan,
year = "2025",
address = "Abu Dhabi, UAE",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.vardial-1.1/",
pages = "1--8",
abstract = "The VarDial Evaluation Campaign 2025 was organized as part of the twelfth workshop on Natural Language Processing for Similar Languages, Varieties and Dialects (VarDial), colocated with COLING 2025. It consisted of one shared task with three subtasks: intent detection, slot filling and dialect identification for Norwegian dialects. This report presents the results of this shared task. Four participating teams have submitted systems with very high performance ({\ensuremath{>}} 97{\%} accuracy) for intent detection, whereas slot detection and dialect identification showed to be much more challenging, with respectively span-F1 scores up to 89{\%}, and weighted dialect F1 scores of 84{\%}."
}
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<abstract>The VarDial Evaluation Campaign 2025 was organized as part of the twelfth workshop on Natural Language Processing for Similar Languages, Varieties and Dialects (VarDial), colocated with COLING 2025. It consisted of one shared task with three subtasks: intent detection, slot filling and dialect identification for Norwegian dialects. This report presents the results of this shared task. Four participating teams have submitted systems with very high performance (\ensuremath> 97% accuracy) for intent detection, whereas slot detection and dialect identification showed to be much more challenging, with respectively span-F1 scores up to 89%, and weighted dialect F1 scores of 84%.</abstract>
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%0 Conference Proceedings
%T Findings of the VarDial Evaluation Campaign 2025: The NorSID Shared Task on Norwegian Slot, Intent and Dialect Identification
%A Scherrer, Yves
%A van der Goot, Rob
%A Mæhlum, Petter
%Y Scherrer, Yves
%Y Jauhiainen, Tommi
%Y Ljubešić, Nikola
%Y Nakov, Preslav
%Y Tiedemann, Jorg
%Y Zampieri, Marcos
%S Proceedings of the 12th Workshop on NLP for Similar Languages, Varieties and Dialects
%D 2025
%8 January
%I Association for Computational Linguistics
%C Abu Dhabi, UAE
%F scherrer-etal-2025-findings
%X The VarDial Evaluation Campaign 2025 was organized as part of the twelfth workshop on Natural Language Processing for Similar Languages, Varieties and Dialects (VarDial), colocated with COLING 2025. It consisted of one shared task with three subtasks: intent detection, slot filling and dialect identification for Norwegian dialects. This report presents the results of this shared task. Four participating teams have submitted systems with very high performance (\ensuremath> 97% accuracy) for intent detection, whereas slot detection and dialect identification showed to be much more challenging, with respectively span-F1 scores up to 89%, and weighted dialect F1 scores of 84%.
%U https://aclanthology.org/2025.vardial-1.1/
%P 1-8
Markdown (Informal)
[Findings of the VarDial Evaluation Campaign 2025: The NorSID Shared Task on Norwegian Slot, Intent and Dialect Identification](https://aclanthology.org/2025.vardial-1.1/) (Scherrer et al., VarDial 2025)
ACL