Papers by Jesujoba O. Alabi
Adapting Pre-trained Language Models to African Languages via Multilingual Adaptive Fine-Tuning (2022.coling-1)
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| Challenge: | Multilingual pre-trained language models have shown impressive performance on several downstream tasks for both high-resourced and low-resource languages. |
| Approach: | They propose to apply multilingual adaptive fine-tuning to 17 most-resourced African languages and three other high-resource languages to encourage cross-lingual transfer learning. |
| Outcome: | The proposed approach is competitive to LAFT on individual languages while requiring significantly less disk space. |
Few-Shot Pidgin Text Adaptation via Contrastive Fine-Tuning (2022.coling-1)
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| Challenge: | Currently, low resource languages are not supported by proper translation systems or parallel corpus. |
| Approach: | They propose to fine-tune the pretrained language models to generate utterances in English-to-Pidgin by leveraging the proximity of the source and target languages and using positive and negative examples in constrastive training objectives. |
| Outcome: | The proposed method is sufficient to generate utterances in English-to-Pidgin, which are two closely-related languages. |