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Multilingual language models have been a crucial breakthrough as they considerably reduce the need of data for under-resourced languages.
Roberta: A robustly optimized BERT pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 1907
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Distilbert, a distilled version of BERT: smaller, faster, cheaper and lighter
Victor Sanh, Lysandre Debut, Julien Chaumond, and Thomas Wolf. 2019 · 1910
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Huggingface’s transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Rémi Louf, Morgan Funtowicz, and Jamie Brew. 2019 · 1910
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Multilingual is not enough: BERT for finnish
Antti Virtanen, Jenna Kanerva, Rami Ilo, Jouni Luoma, Juhani Luotolahti, Tapio Salakoski, Filip Ginter, and Sampo Pyysalo. 2019 · 1912
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Wietse de Vries, Andreas van Cranenburgh, Arianna Bisazza, Tommaso Caselli, Gertjan van Noord, and Malvina Nissim. 2019 · 1912
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SemEval-2012 task 6: A pilot on semantic textual similarity
Eneko Agirre, Daniel Cer, Mona Diab, and Aitor Gonzalez-Agirre. 2012 · 2012
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Parallel data, tools and interfaces in OPUS
Jörg Tiedemann. 2012 · 2012
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Distributed representations of sentences and documents
Quoc V. Le and Tomás Mikolov. 2014 · 2014
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caWaC – a web corpus of Catalan and its application to language modeling and machine translation
Nikola Ljubešić and Antonio Toral. 2014 · 2014
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SQuAD: 100,000+ questions for machine comprehension of text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang. 2016 · 2016
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Enriching word vectors with subword information
Piotr Bojanowski, Edouard Grave, Armand Joulin, and Tomas Mikolov. 2017 · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Cited alongside, same era.
Data statements for natural language processing: Toward mitigating system bias and enabling better science
Emily M. Bender and Batya Friedman. 2018 · 2018
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Slavic language identification using cascade classifier approach
D. Kosmajac and V. Keselj. 2018 · 2018
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Improving language understanding by generative pre-training
Alec Radford and Ilya Sutskever. 2018 · 2018
Cited alongside, same era.
Cross-lingual language model pretraining
Alexis Conneau and Guillaume Lample. 2019 · 2019
Cited alongside, same era.
BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
On the cross-lingual transferability of monolingual representations
Mikel Artetxe, Sebastian Ruder, and Dani Yogatama. 2020 · 2020
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Language models are few-shot learners
Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020 · 2020
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Unsupervised cross-lingual representation learning at scale
Alexis Conneau, Kartikay Khandelwal, Naman Goyal, Vishrav Chaudhary, Guillaume Wenzek, Francisco Guzmán, Edouard Grave, Myle Ott, Luke Zettlemoyer, and Veselin Stoyanov. 2020 · 2020
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FQuAD: French question answering dataset
Martin d’Hoffschmidt, Wacim Belblidia, Quentin Heinrich, Tom Brendlé, and Maxime Vidal. 2020 · 2020
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The state and fate of linguistic diversity and inclusion in the NLP world
Pratik Joshi, Sebastin Santy, Amar Budhiraja, Kalika Bali, and Monojit Choudhury. 2020 · 2020
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Cited alongside, same era.
fairseq: A fast, extensible toolkit for sequence modeling
Myle Ott, Sergey Edunov, Alexei Baevski, Angela Fan, Sam Gross, Nathan Ng, David Grangier, and Michael Auli. 2019 · 2019
Cited alongside, same era.
Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever. 2019 · 2019
Cited alongside, same era.
Asynchronous pipeline for processing huge corpora on medium to low resource infrastructures
Pedro Javier Ortiz Suárez, Benoît Sagot, and Laurent Romary. 2019 · 2019
Cited alongside, same era.
GLUE: A multi-task benchmark and analysis platform for natural language understanding
Alex Wang, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel R. Bowman. 2019 · 2019
Cited alongside, same era.
Give your text representation models some love: the case for Basque
Rodrigo Agerri, Iñaki San Vicente, Jon Ander Campos, Ander Barrena, Xabier Saralegi, Aitor Soroa, and Eneko Agirre. 2020 · 2020
Cited alongside, same era.
Later among the works it cites.
MLQA: Evaluating cross-lingual extractive question answering
Patrick Lewis, Barlas Oguz, Ruty Rinott, Sebastian Riedel, and Holger Schwenk. 2020 · 2020
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CamemBERT: a tasty French language model
Louis Martin, Benjamin Muller, Pedro Javier Ortiz Suárez, Yoann Dupont, Laurent Romary, Éric de la Clergerie, Djamé Seddah, and Benoît Sagot. 2020 · 2020
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What the [mask]? making sense of language-specific bert models
Debora Nozza, Federico Bianchi, and Dirk Hovy. 2020 · 2020
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Wikibert models: deep transfer learning for many languages
Sampo Pyysalo, Jenna Kanerva, Antti Virtanen, and Filip Ginter. 2020 · 2020
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Gottbert: a pure german language model
Raphael Scheible, Fabian Thomczyk, Patric Tippmann, Victor Jaravine, and Martin Boeker. 2020 · 2020
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