The FLoRes Evaluation Datasets for Low-Resource Machine Translation: Nepali-English and Sinhala-English

For machine translation, a vast majority of language pairs in the world are considered low-resource because they have little parallel data available. Besides the technical challenges of learning with limited supervision, it is difficult to evaluate methods trained on low-resource language pairs because of the lack of freely and publicly available benchmarks... (read more)

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