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1
Multilingual Language Model Adaptive Fine-Tuning: A Study on African Languages ...
Abstract: Multilingual pre-trained language models (PLMs) have demonstrated impressive performance on several downstream tasks on both high resourced and low-resourced languages. However, there is still a large performance drop for languages unseen during pre-training, especially African languages. One of the most effective approaches to adapt to a new language is language adaptive fine-tuning (LAFT) -- fine-tuning a multilingual PLM on monolingual texts of a language using the same pre-training objective. However, African languages with large monolingual texts are few, and adapting to each of them individually takes large disk space and limits the cross-lingual transfer abilities of the resulting models because they have been specialized for a single language. In this paper, we perform multilingual adaptive fine-tuning (MAFT) on 17 most-resourced African languages and three other high-resource languages widely spoken on the African continent -- English, French, and Arabic to encourage cross-lingual transfer learning. ... : Accepted to AfricaNLP 2022 (non-archival) ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences
URL: https://arxiv.org/abs/2204.06487
https://dx.doi.org/10.48550/arxiv.2204.06487
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2
MasakhaNER: Named entity recognition for African languages
In: EISSN: 2307-387X ; Transactions of the Association for Computational Linguistics ; https://hal.inria.fr/hal-03350962 ; Transactions of the Association for Computational Linguistics, The MIT Press, 2021, ⟨10.1162/tacl⟩ (2021)
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The effect of domain and diacritics in Yorùbá-English neural machine translation
In: 18th Biennial Machine Translation Summit ; https://hal.inria.fr/hal-03350967 ; 18th Biennial Machine Translation Summit, Aug 2021, Orlando, United States (2021)
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4
The Effect of Domain and Diacritics in Yorùbá-English Neural Machine Translation ...
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5
EdinSaar@WMT21: North-Germanic Low-Resource Multilingual NMT ...
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6
Transfer learning and distant supervision for multilingual Transformer models: A study on African languages
In: 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) ; https://hal.inria.fr/hal-03350901 ; 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), Nov 2020, Punta Cana, Dominica (2020)
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7
Transfer Learning and Distant Supervision for Multilingual Transformer Models: A Study on African Languages ...
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Massive vs. Curated Word Embeddings for Low-Resourced Languages. The Case of Yorùbá and Twi ...
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