Papers by Ekaterina Garmash

1 papers
Connecting degree and polarity: An artificial language learning study (2023.emnlp-main)

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Challenge: Existing studies have shown that degree modifiers are related to sentence polarity, but they are not related to the grammatical number of an expression.
Approach: They propose to generalize degree modifiers to their polarity sensitivity in pre-trained language models by applying the Artificial Language Learning experimental paradigm from psycholinguistics to a neural language model.
Outcome: The proposed generalisations are consistent with existing linguistic observations that relate de-gree semantics to polarity sensitivity, including the main one: low degree semantics is associated with preference towards positive polarities.

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