--- license: apache-2.0 language: - ca - nl - fr - af - ga - gd - ms - oc --- # Dataset Summary This is a variation of **mMARCO** by Bonifacio et al. used for the "Improving Low-Resource Retrieval Effectiveness using Zero-Shot Linguistic Similarity Transfer" ECIR2025 paper. The source code for the paper can be found [here](https://github.com/andreaschari/linguistic-transfer) **mMARCO** is a multilingual version of the [MS MARCO passage ranking dataset](https://microsoft.github.io/msmarco/). For more information, checkout the original **mMARCO** papers: * [**mMARCO: A Multilingual Version of the MS MARCO Passage Ranking Dataset**](https://arxiv.org/abs/2108.13897) * [**A cost-benefit analysis of cross-lingual transfer methods**](https://arxiv.org/abs/2105.06813) # Dataset Structure `queries/` contains both the translated dev queries used for evaluation under `/dev_small` and the translated train/judged queries used for training under `/train/`. The dev queries are in the following languages: Afrikaans, Catalan, Scottish Gaelic, Malay, Occitan, Sicilian, Cantonese. the train queries are in the following languages: Afrikaans, Catalan. `train_with_negs` contains the triples (query, positive doc, negative doc) used for training the models our ECIR 2025 IR4GOOD paper. # Licensing Information This dataset is released under [Apache license 2.0](https://www.apache.org/licenses/). # Citation Information If you use this dataset, please cite: ``` @article{DBLP:journals/corr/abs-2108-13897, author = {Luiz Bonifacio and Israel Campiotti and Roberto de Alencar Lotufo and Rodrigo Frassetto Nogueira}, title = {mMARCO: {A} Multilingual Version of {MS} {MARCO} Passage Ranking Dataset}, journal = {CoRR}, volume = {abs/2108.13897}, year = {2021}, url = {https://arxiv.org/abs/2108.13897}, eprinttype = {arXiv}, eprint = {2108.13897}, timestamp = {Mon, 20 Mar 2023 15:35:34 +0100}, biburl = {https://dblp.org/rec/journals/corr/abs-2108-13897.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } ```