GD-NLI (Generated Debiased NLI Datasets)

Introduced by Wu et al. in Generating Data to Mitigate Spurious Correlations in Natural Language Inference Datasets

This is a set of debiased Natural Language Inference (NLI) datasets produced by the paper Generating Data to Mitigate Spurious Correlations in Natural Language Inference Datasets. The datasets are constructed by augmenting SNLI or MNLI with data samples that are generated to mitigate the spurious correlations in the original datasets. Please visit this repository for more details.

Citation:

@inproceedings{gen-debiased-nli-2022,
    title = "Generating Data to Mitigate Spurious Correlations in Natural Language Inference Datasets",
    author = "Wu, Yuxiang  and
      Gardner, Matt  and
      Stenetorp, Pontus  and
      Dasigi, Pradeep",
    booktitle = "Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics",
    month = may,
    year = "2022",
    publisher = "Association for Computational Linguistics",
}