lyon-nlp/alloprof

This is a re-edit from the Alloprof dataset (which can be found here : https://huggingface.co/datasets/antoinelb7/alloprof).

For more information about the data source and the features, please refer to the original dataset card made by the authors, along with their paper available here : https://arxiv.org/abs/2302.07738

This re-edition of the dataset is a preprocessed version of the original, in a more ready-to-use format. Essentially, the texts have been cleaned, and data not usable for retrieval has been discarded.

Why a re-edition ?

It has been made for easier usage in the MTEB benchmarking pipeline in order to contribute in the MTEB leaderboard : https://huggingface.co/spaces/mteb/leaderboard.

For more information about the project, please refer to the associated paper : https://arxiv.org/pdf/2210.07316.pdf

Usage

To use the dataset, you need to specify the subset you want (documents or queries) when calling the load_dataset() method. For example, to get the queries use :

from datasets import load_dataset
dataset = load_dataset("lyon-nlp/alloprof", "queries")

Citation

If you use this dataset in your work, please consider citing:

@misc{ciancone2024extending,
      title={Extending the Massive Text Embedding Benchmark to French}, 
      author={Mathieu Ciancone and Imene Kerboua and Marion Schaeffer and Wissam Siblini},
      year={2024},
      eprint={2405.20468},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

@misc{lefebvrebrossard2023alloprof,
      title={Alloprof: a new French question-answer education dataset and its use in an information retrieval case study}, 
      author={Antoine Lefebvre-Brossard and Stephane Gazaille and Michel C. Desmarais},
      year={2023},
      eprint={2302.07738},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}