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Retrieval Disagreement as a Signal: Diagnosing and Steering Multilingual Dense Embedders
Multilingual dense retrievers place all languages in one shared space so that a question finds relevant documents, regardless of which language they are written in. We show that the same question, asked in different languages, retrieves substantially different documents, and this disagreement is not
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