mlsanityData to 7 Oct 2026

Deep Learning for Classical Japanese Literature

arXiv 1812.01718 ↗First posted 3 Dec 2018cs.CV cs.LG stat.MLcited by 415

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Abstract (arXiv)

Much of machine learning research focuses on producing models which perform well on benchmark tasks, in turn improving our understanding of the challenges associated with those tasks. From the perspective of ML researchers, the content of the task itself is largely irrelevant, and thus there have increasingly been calls for benchmark tasks to more heavily focus on problems which are of social or cultural relevance. In this work, we introduce Kuzushiji-MNIST, a dataset which focuses on Kuzushiji (cursive Japanese), as well as two larger, more challenging datasets, Kuzushiji-49 and Kuzushiji-Kanji. Through these datasets, we wish to engage the machine learning community into the world of classical Japanese literature. Dataset available at https://github.com/rois-codh/kmnist

Key facts. Cited by 415 papers in the map (data through 7 Oct 2026). First posted on arXiv 3 Dec 2018.

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Citing papers per year: 2021: 79; 2022: 67; 2023: 68; 2024: 70; 2025: 71; 2026: 60.

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