Papers by Ryan Sie

1 papers
Word Frequency Does Not Predict Grammatical Knowledge in Language Models (2020.emnlp-main)

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Challenge: Neural language models learn the grammatical properties of natural languages to varying degrees of accuracy.
Approach: They focus on subject-verb agreement and reflexive anaphora to investigate whether there are systematic sources of variation in the language models’ accuracy.
Outcome: The proposed model can learn grammatical properties from training data.

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