miniCOIL EN-ES: Sparse Neural Retrieval Across the Language Barrier

Qdrant released miniCOIL EN-ES, a multilingual extension of its miniCOIL v1 sparse neural retriever, following the v1 article's promise to extend the model to languages beyond English. The company said sparse retrievers are hard to adapt to cross-lingual search because exact matching across languages usually requires translation.

Sparse neural retrieval finally started getting more and more attention SPARSEUP https://www.linkup.so/blog/introducing-sparseup-by-linkup , MILCO https://arxiv.org/abs/2510.00671 , sparse encoders in Sentence Transformers https://huggingface.co/blog/train-sparse-encoder … . Well, amazing, we like attention Our miniCOIL v1 https://qdrant.tech/articles/minicoil/ sparse neural retriever article ended with a promise: to keep working on this sparse neural retriever in-depth, improving the model’s quality, and in-width, “extending it to other dense encoders and to languages beyond English.” Here is the next “in-width” step of the miniCOIL saga: to try and cross the language barrier, that is, make the model suitable for multilingual retrieval. It’s a fun challenge, as sparse retrievers are hard to adapt to this scenario: exact matching in cross-lingual text search usually means translation.