BPE-Dropout: Simple and Effective Subword Regularization

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Earlier work this paper cites.

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Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov. 2014 · 1958

Earlier work this paper cites.

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Earlier work this paper cites.

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Earlier work this paper cites.

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Earlier work this paper cites.

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Earlier work this paper cites.

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Earlier work this paper cites.

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Mike Schuster and Kaisuke Nakajima. 2012 · 2012

Earlier work this paper cites.

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Earlier work this paper cites.

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Earlier work this paper cites.

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Cited alongside, same era.

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Later among the works it cites.

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Later among the works it cites.

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Later among the works it cites.

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Later among the works it cites.

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Finding better subword segmentation for neural machine translation

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