Papers by Riki Fujihara

1 papers
Topicalization in Language Models: A Case Study on Japanese (2022.coling-1)

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Challenge: a recent study has shown that neural language models can capture discourse-level preferences in text generation . a particular aspect of discourse is the topic-comment structure .
Approach: They analyze whether neural language models can capture discourse-level preferences in text generation . they use Japanese language and crowdsourced human topicalization judgment data .
Outcome: The proposed model can capture human-like generalizations in discourse-level linguistic aspects.

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