Papers by Gbemileke Onilude

1 papers
Intriguing Properties of Compression on Multilingual Models (2022.emnlp-main)

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Challenge: Multilingual models are dependent on scaling to generalize to a growing number of languages . compression techniques can have disparate effects on model performance for low-resource languages if used sparsely .
Approach: They propose to characterize the impact of sparsifying multilingual pre-trained language models during fine-tuning.
Outcome: The proposed framework characterizes the impact of sparsifying multilingual pre-trained language models during fine-tuning.

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