mlsanityData to 14 Oct 2026

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

arXiv 1810.12885 ↗First posted 30 Oct 2018cs.CLcited by 200

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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.

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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Citing papers per year: 2021: 43; 2022: 39; 2023: 40; 2024: 42; 2025: 22; 2026: 14.

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38 more
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