Forewarned Is Forearmed: When Non-Sequential Embedding Turns into an Anomaly Detector

Elys Allesiardo; Antoine Caubrière; Valentin Vielzeuf

doi:10.63317/58vxg7q9649q

Forewarned Is Forearmed: When Non-Sequential Embedding Turns into an Anomaly Detector

Elys Allesiardo, Antoine Caubrière, Valentin Vielzeuf

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Abstract

This paper offers an in-depth analysis of non-sequential multimodal sentence-level embeddings, with a particular focus on the SONAR model. We demonstrate that certain embedding dimensions are sensitive to perturbations and can serve as indicators of decoding anomalies. By leveraging the consistency between successive encoding and decoding, we successfully build an accurate detector. Additionally, we explore modifying specific dimensions of interest to attempt to correct them. This work underscores the importance of understanding and analyzing the embeddings themselves to enhance the reliability of multimodal representations.

Anthology ID:: 2026.lrec-1.797
Volume:: Proceedings of the Fifteenth Language Resources and Evaluation Conference
Month:: May
Year:: 2026
Address:: Palma de Mallorca, Spain
Editors:: Stelios Piperidis, Núria Bel, Henk van den Heuvel, Nancy Ide, Simon Krek, Antonio Toral
Venue:: LREC
SIG:
Publisher:: ELRA Language Resource Association
Note:
Pages:: 10150–10156
Language:
External URL:: https://lrec.elra.info/lrec2026-main-797
DOI:: 10.63317/58vxg7q9649q
Bibkey:
Cite (ACL):: Elys Allesiardo, Antoine Caubrière, and Valentin Vielzeuf. 2026. Forewarned Is Forearmed: When Non-Sequential Embedding Turns into an Anomaly Detector. In Proceedings of the Fifteenth Language Resources and Evaluation Conference, pages 10150–10156, Palma de Mallorca, Spain. ELRA Language Resource Association.
Cite (Informal):: Forewarned Is Forearmed: When Non-Sequential Embedding Turns into an Anomaly Detector (Allesiardo et al., LREC 2026)
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@inproceedings{allesiardo-etal-2026-forewarned,
    title = "Forewarned Is Forearmed: When Non-Sequential Embedding Turns into an Anomaly Detector",
    author = "Allesiardo, Elys  and
      Caubri{\`e}re, Antoine  and
      Vielzeuf, Valentin",
    editor = "Piperidis, Stelios  and
      Bel, N{\'u}ria  and
      van den Heuvel, Henk  and
      Ide, Nancy  and
      Krek, Simon  and
      Toral, Antonio",
    booktitle = "Proceedings of the Fifteenth Language Resources and Evaluation Conference",
    month = may,
    year = "2026",
    address = "Palma de Mallorca, Spain",
    publisher = "ELRA Language Resource Association",
    url = "https://aclanthology.org/2026.lrec-1.797/",
    doi = "10.63317/58vxg7q9649q",
    pages = "10150--10156",
    abstract = "This paper offers an in-depth analysis of non-sequential multimodal sentence-level embeddings, with a particular focus on the SONAR model. We demonstrate that certain embedding dimensions are sensitive to perturbations and can serve as indicators of decoding anomalies. By leveraging the consistency between successive encoding and decoding, we successfully build an accurate detector. Additionally, we explore modifying specific dimensions of interest to attempt to correct them. This work underscores the importance of understanding and analyzing the embeddings themselves to enhance the reliability of multimodal representations."
}

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%0 Conference Proceedings
%T Forewarned Is Forearmed: When Non-Sequential Embedding Turns into an Anomaly Detector
%A Allesiardo, Elys
%A Caubrière, Antoine
%A Vielzeuf, Valentin
%Y Piperidis, Stelios
%Y Bel, Núria
%Y van den Heuvel, Henk
%Y Ide, Nancy
%Y Krek, Simon
%Y Toral, Antonio
%S Proceedings of the Fifteenth Language Resources and Evaluation Conference
%D 2026
%8 May
%I ELRA Language Resource Association
%C Palma de Mallorca, Spain
%F allesiardo-etal-2026-forewarned
%X This paper offers an in-depth analysis of non-sequential multimodal sentence-level embeddings, with a particular focus on the SONAR model. We demonstrate that certain embedding dimensions are sensitive to perturbations and can serve as indicators of decoding anomalies. By leveraging the consistency between successive encoding and decoding, we successfully build an accurate detector. Additionally, we explore modifying specific dimensions of interest to attempt to correct them. This work underscores the importance of understanding and analyzing the embeddings themselves to enhance the reliability of multimodal representations.
%R 10.63317/58vxg7q9649q
%U https://aclanthology.org/2026.lrec-1.797/
%U https://doi.org/10.63317/58vxg7q9649q
%P 10150-10156

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Markdown (Informal)

[Forewarned Is Forearmed: When Non-Sequential Embedding Turns into an Anomaly Detector](https://aclanthology.org/2026.lrec-1.797/) (Allesiardo et al., LREC 2026)

Forewarned Is Forearmed: When Non-Sequential Embedding Turns into an Anomaly Detector (Allesiardo et al., LREC 2026)

ACL

Elys Allesiardo, Antoine Caubrière, and Valentin Vielzeuf. 2026. Forewarned Is Forearmed: When Non-Sequential Embedding Turns into an Anomaly Detector. In Proceedings of the Fifteenth Language Resources and Evaluation Conference, pages 10150–10156, Palma de Mallorca, Spain. ELRA Language Resource Association.