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GLUE

Pre-trained language models (PrLM) have to carefully manage input units when training on a very large text with a vocabulary consisting of millions of words. Previous works have shown that incorporating span-level information over consecutive words in pre-training could further improve the performance of PrLMs.

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Cite this as

Yi Yang, Chen Zhang, Dawei Song (2024). Dataset: GLUE. https://doi.org/10.57702/byuoeozp

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Additional Info

Field	Value
Created	December 2, 2024
Last update	December 2, 2024
Defined In	https://doi.org/10.48550/arXiv.2201.04467
Citation	https://doi.org/10.48550/arXiv.2305.17197 https://doi.org/10.48550/arXiv.1909.03004 https://doi.org/10.48550/arXiv.2310.14110 https://doi.org/10.48550/arXiv.2405.04513 https://doi.org/10.1073/pnas.2215907120 https://doi.org/10.48550/arXiv.2210.03923 https://doi.org/10.48550/arXiv.2211.07350 https://doi.org/10.48550/arXiv.2106.08823 https://doi.org/10.48550/arXiv.1904.12166 https://doi.org/10.48550/arXiv.2211.09744 https://doi.org/10.48550/arXiv.2108.12848
Author	Yi Yang
More Authors	Chen Zhang Dawei Song
Homepage	https://glue.mlt.io/