# Deep Learning for Classical Japanese Literature

arXiv: https://arxiv.org/abs/1812.01718 · HTML: https://mlsanity.com/paper/1812.01718/

## Key facts

- Cited by 422 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 Dec 2018.

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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
