Datasets › GD-NLI
GD-NLI (Generated Debiased NLI 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",
}
Benchmarks archive 2025-07-28
No leaderboard in the archive resolves to this dataset.
Papers archive 2025-07-28
No paper in the archive has a leaderboard row on this dataset; the archive counts 1 paper for it but never published that list.
Dataset loaders archive 2025-07-28
No loader listed in the archive.
Tasks archive 2025-07-28
License archive 2025-07-28
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Modalities archive 2025-07-28
Languages archive 2025-07-28
Variants archive 2025-07-28
- GD-NLI
1 variant name, as the archive lists them.
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