Papers with term low-resource double bind to

1 papers
The Low-Resource Double Bind: An Empirical Study of Pruning for Low-Resource Machine Translation (2021.findings-emnlp)

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Challenge: Extending state-of-the-art language models to low-resource languages requires addressing what we call the low-Resource double bind.
Approach: They propose a low-resource double bind to refer to the co-occurrence of data limitations and compute resource constraints.
Outcome: The proposed model improves performance on frequent sentences but disparates on infrequent ones.

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