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---
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}
}
``` |