Generative Knowledge Selection for Knowledge-Grounded Dialogues
Generative Knowledge Selection for Knowledge-Grounded Dialogues
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Ithaca: Cornell University Library, arXiv.org
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English
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Ithaca: Cornell University Library, arXiv.org
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Contents
Knowledge selection is the key in knowledge-grounded dialogues (KGD), which aims to select an appropriate knowledge snippet to be used in the utterance based on dialogue history. Previous studies mainly employ the classification approach to classify each candidate snippet as "relevant" or "irrelevant" independently. However, such approaches neglect...
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Full title
Generative Knowledge Selection for Knowledge-Grounded Dialogues
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TN_cdi_proquest_journals_2799917950
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2799917950
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E-ISSN
2331-8422
