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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 8 of 8 1 Multilingual Language Model Adaptive Fine-Tuning: A Study on African Languages ... Alabi, Jesujoba O.; Adelani, David Ifeoluwa; Mosbach, Marius. - : arXiv, 2022 BASE Show details 2 MasakhaNER: Named entity recognition for African languages Adelani, David,; Abbott, Jade; Neubig, Graham... 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) BASE Show details 3 The effect of domain and diacritics in Yorùbá-English neural machine translation Adelani, David,; Ruiter, Dana; Alabi, Jesujoba,... In: 18th Biennial Machine Translation Summit ; https://hal.inria.fr/hal-03350967 ; 18th Biennial Machine Translation Summit, Aug 2021, Orlando, United States (2021) BASE Show details 4 The Effect of Domain and Diacritics in Yorùbá-English Neural Machine Translation ... Adelani, David I.; Ruiter, Dana; Alabi, Jesujoba O.. - : arXiv, 2021 BASE Show details 5 EdinSaar@WMT21: North-Germanic Low-Resource Multilingual NMT ... Tchistiakova, Svetlana; Alabi, Jesujoba; Chowdhury, Koel Dutta. - : arXiv, 2021 BASE Show details 6 Transfer learning and distant supervision for multilingual Transformer models: A study on African languages Hedderich, Michael,; Adelani, David,; Zhu, Dawei; Alabi, Jesujoba; Markus, Udia; Klakow, Dietrich 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) Abstract: International audience ; Multilingual transformer models like mBERT and XLM-RoBERTa have obtained great improvements for many NLP tasks on a variety of languages. However, recent works also showed that results from high-resource languages could not be easily transferred to realistic, low-resource scenarios. In this work, we study trends in performance for different amounts of available resources for the three African languages Hausa, isiXhosa and Yorùbá on both NER and topic classification. We show that in combination with transfer learning or distant supervision, these models can achieve with as little as 10 or 100 labeled sentences the same performance as baselines with much more supervised training data. However, we also find settings where this does not hold. Our discussions and additional experiments on assumptions such as time and hardware restrictions highlight challenges and opportunities in low-resource learning. Keyword: [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL] URL: https://hal.inria.fr/hal-03350901 https://hal.inria.fr/hal-03350901/file/hedderich_EMNLP2020.pdf https://hal.inria.fr/hal-03350901/document BASE Hide details 7 Transfer Learning and Distant Supervision for Multilingual Transformer Models: A Study on African Languages ... Hedderich, Michael A.; Adelani, David; Zhu, Dawei. - : arXiv, 2020 BASE Show details 8 Massive vs. Curated Word Embeddings for Low-Resourced Languages. The Case of Yorùbá and Twi ... Alabi, Jesujoba O.; Amponsah-Kaakyire, Kwabena; Adelani, David I.. - : arXiv, 2019 BASE Show details

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