pietrolesci/robust_nli
Overview Original dataset is available in the original Github repo. This dataset is a collection of NLI benchmarks constructed as described in the paper An Empirical Study on Model-agnostic Debiasing Strategies for Robust Natural Language Inference published at CoNLL 2020. Dataset curation No specific curation for this dataset. Label encoding follows exactly what is reported in the paper by the authors. Also, from the paper: all the following datasets are… See the full description on the dataset page: https://huggingface.co/datasets/pietrolesci/robust_nli.
| Author / organization | pietrolesci |
|---|---|
| Downloads | 188 (as reported by Hugging Face) |
| Likes | 2 |
| Created | 25 April 2022 |
| Last updated at source | 25 April 2022 |
Popularity, last 3 days
188 now (-7 since 2026-10-16). Counts as reported by the source, snapshotted daily by Silytics.
Connected in the knowledge graph
- sileod/deberta-v3-base-tasksource-nliModel · used to train
- tasksource/deberta-base-long-nliModel · used to train
- sileod/deberta-v3-large-tasksource-nliModel · used to train
- tasksource/deberta-small-long-nliModel · used to train
Recent changes
- 17 Oct 2026 Description: Overview Original dataset is available in the original Github repo. This dataset is a collection of NLI benchmarks constructed as described in the paper An Empirical Study on Model-agnostic Debiasing Strategies for Robust Natural Language I → Overview Original dataset is available in the original Github repo. This dataset is a collection of NLI benchmarks constructed as described in the paper An Empirical Study on Model-agnostic Debiasing Strategies for Robust Natural Language I
Changes detected by Silytics between refreshes of the source.
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Silytics shows public metadata from Hugging Face and links to the original. Information may be incomplete or out of date. Last refreshed 18 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.