Forewarned is Forearmed: When Non-Sequential Embedding Turns Into an Anomaly Detector

Elys Allesiardo; Antoine Caubrière; Valentin Vielzeuf

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arXiv · 2606.30196

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.

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Elys Allesiardo, Antoine Caubrière, Valentin Vielzeuf. 2026-06-29. Forewarned is Forearmed: When Non-Sequential Embedding Turns Into an Anomaly Detector. https://arxiv.org/abs/2606.30196

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