Bayesian Multi-Task Transfer Learning for Soft Prompt Tuning

Cited 0 time in webofscience Cited 0 time in scopus
  • Hit : 69
  • Download : 0
DC FieldValueLanguage
dc.contributor.authorLee, Haejuko
dc.contributor.authorJeong, Minchanko
dc.contributor.authorYun, Seyoungko
dc.contributor.authorKim, Kee-Eungko
dc.date.accessioned2023-12-08T02:01:27Z-
dc.date.available2023-12-08T02:01:27Z-
dc.date.created2023-12-07-
dc.date.created2023-12-07-
dc.date.created2023-12-07-
dc.date.issued2023-12-08-
dc.identifier.citationThe 2023 Conference on Empirical Methods in Natural Language Processing-
dc.identifier.urihttp://hdl.handle.net/10203/316044-
dc.languageEnglish-
dc.publisher2023 Association for Computational Linguistics-
dc.titleBayesian Multi-Task Transfer Learning for Soft Prompt Tuning-
dc.typeConference-
dc.type.rimsCONF-
dc.citation.publicationnameThe 2023 Conference on Empirical Methods in Natural Language Processing-
dc.identifier.conferencecountryUS-
dc.identifier.conferencelocationResorts World Convention Centre-
dc.contributor.localauthorYun, Seyoung-
dc.contributor.localauthorKim, Kee-Eung-
dc.contributor.nonIdAuthorLee, Haeju-
Appears in Collection
AI-Conference Papers(학술대회논문)
Files in This Item
There are no files associated with this item.

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0