# ReCoRD: Bridging the Gap between Human and Machine Commonsense Reading Comprehension

arXiv: https://arxiv.org/abs/1810.12885 · HTML: https://mlsanity.com/paper/1810.12885/

## Key facts

- Cited by 200 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 Oct 2018.

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## Abstract (arXiv)

We present a large-scale dataset, ReCoRD, for machine reading comprehension requiring commonsense reasoning. Experiments on this dataset demonstrate that the performance of state-of-the-art MRC systems fall far behind human performance. ReCoRD represents a challenge for future research to bridge the gap between human and machine commonsense reading comprehension. ReCoRD is available at http://nlp.jhu.edu/record.