Code-switching creates a fundamental performance bottleneck for multilingual retrievers, causing drops of up to 27% on new benchmarks CSR-L and CS-MTEB, with embedding divergence as the key cause and vocabulary expansion insufficient to fix it.
Boosting Zero-shot Cross-lingual Retrieval by Training on Artificially Code-Switched Data
3 Pith papers cite this work, alongside 3 external citations. Polarity classification is still indexing.
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Optimal interpolation of query embeddings from parallel translations outperforms the best monolingual query in 88/105 cases on mMARCO, showing English-driven asymmetry and negative correlation with typological distance.
WikiDIR is a seven-dialect German retrieval benchmark showing that lexical and zero-shot neural methods struggle with dialect variation, while document translation substantially reduces the gap.
citing papers explorer
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Code-Switching Information Retrieval: Benchmarks, Analysis, and the Limits of Current Retrievers
Code-switching creates a fundamental performance bottleneck for multilingual retrievers, causing drops of up to 27% on new benchmarks CSR-L and CS-MTEB, with embedding divergence as the key cause and vocabulary expansion insufficient to fix it.
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When Does Mixing Help? Analyzing Query Embedding Interpolation in Multilingual Dense Retrieval
Optimal interpolation of query embeddings from parallel translations outperforms the best monolingual query in 88/105 cases on mMARCO, showing English-driven asymmetry and negative correlation with typological distance.
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Cross-Dialect Information Retrieval: Information Access in Low-Resource and High-Variance Languages
WikiDIR is a seven-dialect German retrieval benchmark showing that lexical and zero-shot neural methods struggle with dialect variation, while document translation substantially reduces the gap.