Datasets › CosmosQA

CosmosQA

Introduced by Lifu Huang et al. in Cosmos QA: Machine Reading Comprehension with Contextual Commonsense Reasoning1 Jan 2019 archive 2025-07-28

CosmosQA is a large-scale dataset of 35.6K problems that require commonsense-based reading comprehension, formulated as multiple-choice questions. It focuses on reading between the lines over a diverse collection of people’s everyday narratives, asking questions concerning on the likely causes or effects of events that require reasoning beyond the exact text spans in the context.

Source: Teaching Pretrained Models with Commonsense Reasoning: A Preliminary KB-Based Approach Image Source: https://arxiv.org/pdf/1909.00277.pdf

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 102 papers for it but never published that list.

Dataset loaders archive 2025-07-28

3 loaders as listed in the archive; links are outbound and not re-checked here.

Tasks archive 2025-07-28

License archive 2025-07-28

Unknown

Modalities archive 2025-07-28

Languages archive 2025-07-28

Variants archive 2025-07-28

  • CosmosQA

1 variant name, as the archive lists them.

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