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XTREME-S: Evaluating Cross-lingual Speech Representations ...
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One Country, 700+ Languages: NLP Challenges for Underrepresented Languages and Dialects in Indonesia ...
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Expanding Pretrained Models to Thousands More Languages via Lexicon-based Adaptation ...
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MasakhaNER: Named entity recognition for African languages
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Adelani, David,; Abbott, Jade; Neubig, Graham; D'Souza, Daniel; Kreutzer, Julia; Lignos, Constantine; Palen-Michel, Chester; Buzaaba, Happy; Rijhwani, Shruti; Ruder, Sebastian; Mayhew, Stephen; Abebe Azime, Israel; Muhammad, Shamsuddeen,; Chinenye Emezue, Chris; Nakatumba-Nabende, Joyce; Ogayo, Perez; Aremu, Anuoluwapo; Gitau, Catherine; Mbaye, Derguene; Alabi, Jesujoba; Yimam, Seid,; Rabiu Gwadabe, Tajuddeen; Ezeani, Ignatius; Niyongabo, Rubungo,; Mukiibi, Jonathan; Otiende, Verrah; Orife, Iroro; David, Davis; Ngom, Samba; Adewumi, Tosin; Rayson, Paul; Adeyemi, Mofetoluwa; Muriuki, Gerald; Anebi, Emmanuel; Chukwuneke, Chiamaka; Odu, Nkiruka; Wairagala, Eric,; Oyerinde, Samuel; Siro, Clemencia; Saul Bateesa, Tobius; Oloyede, Temilola; Wambui, Yvonne; Akinode, Victor; Nabagereka, Deborah; Katusiime, Maurice; Awokoya, Ayodele; Mboup, Mouhamadane; Gebreyohannes, Dibora; Tilaye, Henok; Nwaike, Kelechi; Wolde, Degaga; Faye, Abdoulaye; Sibanda, Blessing; Ahia, Orevaoghene; Dossou, Bonaventure,; Ogueji, Kelechi; Thierno, Ibrahima; DIALLO, Abdoulaye; Akinfaderin, Adewale; Marengereke, Tendai; Osei, Salomey
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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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Abstract:
International audience ; We take a step towards addressing the underrepresentation of the African continent in NLP research by bringing together different stakeholders to create the first large, publicly available, high-quality dataset for named entity recognition (NER) in ten African languages. We detail the characteristics of these languages to help researchers and practitioners better understand the challenges they pose for NER tasks. We analyze our datasets and conduct an extensive empirical evaluation of stateof-the-art methods across both supervised and transfer learning settings. Finally, we release the data, code, and models to inspire future research on African NLP. 1
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Keyword:
[INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]
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URL: https://hal.inria.fr/hal-03350962 https://doi.org/10.1162/tacl https://hal.inria.fr/hal-03350962/document https://hal.inria.fr/hal-03350962/file/adelani_TACL2021.pdf
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Charformer: Fast Character Transformers via Gradient-based Subword Tokenization ...
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XTREME-R: Towards More Challenging and Nuanced Multilingual Evaluation ...
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Efficient Test Time Adapter Ensembling for Low-resource Language Varieties ...
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XTREME-R: Towards More Challenging and Nuanced Multilingual Evaluation ...
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A Call for More Rigor in Unsupervised Cross-lingual Learning ...
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Rethinking embedding coupling in pre-trained language models ...
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MAD-X: An Adapter-Based Framework for Multi-Task Cross-Lingual Transfer ...
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How Good is Your Tokenizer? On the Monolingual Performance of Multilingual Language Models ...
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UNKs Everywhere: Adapting Multilingual Language Models to New Scripts ...
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MAD-X: An Adapter-Based Framework for Multi-Task Cross-Lingual Transfer ...
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Morphologically Aware Word-Level Translation
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In: Proceedings of the 28th International Conference on Computational Linguistics (2020)
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XTREME: A Massively Multilingual Multi-task Benchmark for Evaluating Cross-lingual Generalization ...
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