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Pre-trained contextual representations have led to dramatic performance improvements on a range of downstream tasks.
RoBERTa: A robustly optimized BERT pretraining approach
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Fine-grained analysis of sentence embeddings using auxiliary prediction tasks
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Piotr Bojanowski, Edouard Grave, Armand Joulin, and Tomas Mikolov. 2017 · 2017
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ALBERT: A lite BERT for self-supervised learning of language representations
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Marrying universal dependencies and universal morphology
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Deep contextualized word representations
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Language modeling teaches you more than translation does: Lessons learned through auxiliary syntactic task analysis
Kelly Zhang and Samuel Bowman. 2018 · 2018
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Analysis methods in neural language processing: A survey
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Pareto probing: Trading off accuracy for complexity
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Exploring the limits of transfer learning with a unified text-to-text transformer
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Information-theoretic probing with minimum description length
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Transformers: State-of-the-art natural language processing
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