{"url":"/dataset/gd-nli","name":"GD-NLI","full_name":"Generated Debiased NLI Datasets","description_markdown":"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](https://arxiv.org/abs/2203.12942). 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](https://github.com/jimmycode/gen-debiased-nli) for more details.\r\n\r\nCitation:\r\n```\r\n@inproceedings{gen-debiased-nli-2022,\r\n    title = \"Generating Data to Mitigate Spurious Correlations in Natural Language Inference Datasets\",\r\n    author = \"Wu, Yuxiang  and\r\n      Gardner, Matt  and\r\n      Stenetorp, Pontus  and\r\n      Dasigi, Pradeep\",\r\n    booktitle = \"Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics\",\r\n    month = may,\r\n    year = \"2022\",\r\n    publisher = \"Association for Computational Linguistics\",\r\n}\r\n```","description_withheld":null,"homepage":"https://github.com/jimmycode/gen-debiased-nli","introduced_date":"2022-03-24","introduced_date_note":null,"introduced_by":{"paper":"/paper/generating-data-to-mitigate-spurious-1","title":"Generating Data to Mitigate Spurious Correlations in Natural Language Inference Datasets","first_author":"Yuxiang Wu","url":null},"license":null,"modalities":[{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"Natural Language Inference","url":"/task/natural-language-inference","datasets_with_task":"/datasets/task/natural-language-inference"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["GD-NLI"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}