Diversity patterns run deep: Impact of diversity intake on multiword expression identification

Mathilde Deletombe; Manon Scholivet; Louis Estève; Thomas Lavergne; Agata Savary

Diversity patterns run deep: Impact of diversity intake on multiword expression identification

Mathilde Deletombe, Manon Scholivet, Louis Estève, Thomas Lavergne, Agata Savary

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Abstract

Multiword expressions (MWEs) are good examples of a phenomenon where identification systems struggle with generalisation: MWE present in the test set but absent in the training set are rarely identified. This raises the question of the diversity of the test set, relative to that of the train set, and how this impacts performance. We set out to measure how much diversity of a train corpus increases when adding individual MWEs from the test corpus, and how this increase impacts MWE identification performance. We measure diversity across a three-dimension framework and find mostly consistent negative correlations with performance in 14 languages and 8 systems.

Anthology ID:: 2026.mwe-1.13
Volume:: Proceedings of the 22nd Workshop on Multiword Expressions (MWE 2026)
Month:: March
Year:: 2026
Address:: Rabat, Marocco
Editors:: Atul Kr. Ojha, Verginica Barbu Mititelu, Mathieu Constant, Ivelina Stoyanova, A. Seza Doğruöz, Alexandre Rademaker
Venues:: MWE | WS
SIG:
Publisher:: Association for Computational Linguistics
Note:
Pages:: 110–116
Language:
URL:: https://aclanthology.org/2026.mwe-1.13/
DOI:
Bibkey:
Cite (ACL):: Mathilde Deletombe, Manon Scholivet, Louis Estève, Thomas Lavergne, and Agata Savary. 2026. Diversity patterns run deep: Impact of diversity intake on multiword expression identification. In Proceedings of the 22nd Workshop on Multiword Expressions (MWE 2026), pages 110–116, Rabat, Marocco. Association for Computational Linguistics.
Cite (Informal):: Diversity patterns run deep: Impact of diversity intake on multiword expression identification (Deletombe et al., MWE 2026)
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PDF:: https://aclanthology.org/2026.mwe-1.13.pdf

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@inproceedings{deletombe-etal-2026-diversity,
    title = "Diversity patterns run deep: Impact of diversity intake on multiword expression identification",
    author = "Deletombe, Mathilde  and
      Scholivet, Manon  and
      Est{\`e}ve, Louis  and
      Lavergne, Thomas  and
      Savary, Agata",
    editor = {Ojha, Atul Kr.  and
      Mititelu, Verginica Barbu  and
      Constant, Mathieu  and
      Stoyanova, Ivelina  and
      Do{\u{g}}ru{\"o}z, A. Seza  and
      Rademaker, Alexandre},
    booktitle = "Proceedings of the 22nd Workshop on Multiword Expressions ({MWE} 2026)",
    month = mar,
    year = "2026",
    address = "Rabat, Marocco",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2026.mwe-1.13/",
    pages = "110--116",
    ISBN = "979-8-89176-363-0",
    abstract = "Multiword expressions (MWEs) are good examples of a phenomenon where identification systems struggle with generalisation: MWE present in the test set but absent in the training set are rarely identified. This raises the question of the diversity of the test set, relative to that of the train set, and how this impacts performance. We set out to measure how much diversity of a train corpus increases when adding individual MWEs from the test corpus, and how this increase impacts MWE identification performance. We measure diversity across a three-dimension framework and find mostly consistent negative correlations with performance in 14 languages and 8 systems."
}

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%0 Conference Proceedings
%T Diversity patterns run deep: Impact of diversity intake on multiword expression identification
%A Deletombe, Mathilde
%A Scholivet, Manon
%A Estève, Louis
%A Lavergne, Thomas
%A Savary, Agata
%Y Ojha, Atul Kr.
%Y Mititelu, Verginica Barbu
%Y Constant, Mathieu
%Y Stoyanova, Ivelina
%Y Doğruöz, A. Seza
%Y Rademaker, Alexandre
%S Proceedings of the 22nd Workshop on Multiword Expressions (MWE 2026)
%D 2026
%8 March
%I Association for Computational Linguistics
%C Rabat, Marocco
%@ 979-8-89176-363-0
%F deletombe-etal-2026-diversity
%X Multiword expressions (MWEs) are good examples of a phenomenon where identification systems struggle with generalisation: MWE present in the test set but absent in the training set are rarely identified. This raises the question of the diversity of the test set, relative to that of the train set, and how this impacts performance. We set out to measure how much diversity of a train corpus increases when adding individual MWEs from the test corpus, and how this increase impacts MWE identification performance. We measure diversity across a three-dimension framework and find mostly consistent negative correlations with performance in 14 languages and 8 systems.
%U https://aclanthology.org/2026.mwe-1.13/
%P 110-116

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Markdown (Informal)

[Diversity patterns run deep: Impact of diversity intake on multiword expression identification](https://aclanthology.org/2026.mwe-1.13/) (Deletombe et al., MWE 2026)

Diversity patterns run deep: Impact of diversity intake on multiword expression identification (Deletombe et al., MWE 2026)

ACL

Mathilde Deletombe, Manon Scholivet, Louis Estève, Thomas Lavergne, and Agata Savary. 2026. Diversity patterns run deep: Impact of diversity intake on multiword expression identification. In Proceedings of the 22nd Workshop on Multiword Expressions (MWE 2026), pages 110–116, Rabat, Marocco. Association for Computational Linguistics.