Papers with language modeling benchmarks

1 papers
A Systematic Assessment of Syntactic Generalization in Neural Language Models (2020.acl-main)

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Challenge: Existing work on syntactic knowledge models has not provided a clear picture of the properties required to produce proper syntaktic generalizations.
Approach: They propose to evaluate syntactic knowledge of language models by varying model architectures . they find substantial differences in syntaktic generalization performance by model architecture .
Outcome: The proposed model architectures outperform other architectures on a set of 34 English-language syntactic test suites.

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