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Large-scale pretrained language models have become ubiquitous in Natural Language Processing.
75 languages, 1 model: Parsing universal dependencies universally
Daniel Kondratyuk. 2019 · 1904
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Introducing ronec–the romanian named entity corpus
Stefan Daniel Dumitrescu and Andrei-Marius Avram. 2019 · 1909
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Parallel data, tools and interfaces in opus
Jörg Tiedemann. 2012 · 2012
Earlier work this paper cites.
Semeval-2013 task 9: Extraction of drug-drug interactions from biomedical texts (ddiextraction 2013)
Isabel Segura Bedmar, Paloma Martínez, and María Herrero Zazo. 2013 · 2013
Earlier work this paper cites.
The romanian treebank annotated according to universal dependencies
Verginica Barbu Mititelu, Radu Ion, Radu Simionescu, Elena Irimia, and Cenel-Augusto Perez. 2016 · 2016
Earlier work this paper cites.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018 · 2018
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Conll 2018 shared task: Multilingual parsing from raw text to universal dependencies
Daniel Zeman, Jan Hajic, Martin Popel, Martin Potthast, Milan Straka, Filip Ginter, Joakim Nivre, and Slav Petrov. 2018 · 2018
Earlier work this paper cites.
What does bert look at? an analysis of bert’s attention
Kevin Clark, Urvashi Khandelwal, Omer Levy, and Christopher D. Manning. 2019 · 2019
Cited alongside, same era.
Cross-lingual language model pretraining
Guillaume Lample and Alexis Conneau. 2019 · 2019
Cited alongside, same era.
Albert: A lite bert for self-supervised learning of language representations
Zhenzhong Lan, Mingda Chen, Sebastian Goodman, Kevin Gimpel, Piyush Sharma, and Radu Soricut. 2019 · 2019
Cited alongside, same era.
Flaubert: Unsupervised language model pre-training for french
Hang Le, Loïc Vial, Jibril Frej, Vincent Segonne, Maximin Coavoux, Benjamin Lecouteux, Alexandre Allauzen, Benoît Crabbé, Laurent Besacier, and Didier Schwab. 2019 · 2019
Cited alongside, same era.
Bert rediscovers the classical nlp pipeline
Ian Tenney, Dipanjan Das, and Ellie Pavlick. 2019 · 2019
Later among the works it cites.
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 · 2019
Later among the works it cites.
Wietse de Vries, Andreas van Cranenburgh, Arianna Bisazza, Tommaso Caselli, Gertjan van Noord, and Malvina Nissim. 2019 · 2019
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Xlnet: Generalized autoregressive pretraining for language understanding
Zhilin Yang, Zihang Dai, Yiming Yang, Jaime Carbonell, Ruslan Salakhutdinov, and Quoc V. Le. 2019 · 2019
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Paul Michel, Omer Levy, and Graham Neubig. 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.
Distilbert, a distilled version of bert: smaller, faster, cheaper and lighter
Victor Sanh, Lysandre Debut, Julien Chaumond, and Thomas Wolf. 2019 · 2019
Cited alongside, same era.
Yang You, Jing Li, Sashank Reddi, Jonathan Hseu, Sanjiv Kumar, Srinadh Bhojanapalli, Xiaodan Song, James Demmel, Kurt Keutzer, and Cho-Jui Hsieh. 2019 · 2019
Later among the works it cites.
Electra: Pre-training text encoders as discriminators rather than generators
Kevin Clark, Minh-Thang Luong, Quoc V. Le, and Christopher D. Manning. 2020 · 2020
Closest in time.
A primer in bertology: What we know about how bert works
Anna Rogers, Olga Kovaleva, and Anna Rumshisky. 2020 · 2020
Closest in time.