Zobrazeno 1 - 10
of 30
pro vyhledávání: '"Bartko, Andrew"'
Autor:
Li, Jiacheng, Katsis, Yannis, Baldwin, Tyler, Kim, Ho-Cheol, Bartko, Andrew, McAuley, Julian, Hsu, Chun-Nan
Knowledge-enhanced pre-trained models for language representation have been shown to be more effective in knowledge base construction tasks (i.e.,~relation extraction) than language models such as BERT. These knowledge-enhanced language models incorp
Externí odkaz:
http://arxiv.org/abs/2208.09625
Autor:
Hogan, William, Huang, Molly, Katsis, Yannis, Baldwin, Tyler, Kim, Ho-Cheol, Baeza, Yoshiki Vazquez, Bartko, Andrew, Hsu, Chun-Nan
Publikováno v:
3rd Conference on Automated Knowledge Base Construction (2021)
Relation extraction in the biomedical domain is a challenging task due to a lack of labeled data and a long-tail distribution of fact triples. Many works leverage distant supervision which automatically generates labeled data by pairing a knowledge g
Externí odkaz:
http://arxiv.org/abs/2110.12501
Autor:
McDonald, Daniel, Jiang, Yueyu, Balaban, Metin, Cantrell, Kalen, Zhu, Qiyun, Gonzalez, Antonio, Morton, James T., Nicolaou, Giorgia, Parks, Donovan H., Karst, Søren M., Albertsen, Mads, Hugenholtz, Philip, DeSantis, Todd, Song, Se Jin, Bartko, Andrew, Havulinna, Aki S., Jousilahti, Pekka, Cheng, Susan, Inouye, Michael, Niiranen, Teemu
Publikováno v:
Nature Biotechnology; May2024, Vol. 42 Issue 5, p715-718, 4p
Publikováno v:
Nature Physics 2, 557 (2006)
The rate at which excited charge carriers relax to their equilibrium state affects many aspects of the performance of nanoscale devices, including switching speed, carrier mobility and luminescent efficiency. Better understanding of the processes tha
Externí odkaz:
http://arxiv.org/abs/cond-mat/0608396
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Publikováno v:
Science, 2001 Jan 01. 291(5501), 103-106.
Externí odkaz:
https://www.jstor.org/stable/3082182
Autor:
Li, Jiacheng, Katsis, Yannis, Baldwin, Tyler, Kim, Ho-Cheol, Bartko, Andrew, McAuley, Julian, Hsu, Chun-Nan
Publikováno v:
Proceedings of the 31st ACM International Conference on Information & Knowledge Management.
Knowledge-enhanced pre-trained models for language representation have been shown to be more effective in knowledge base construction tasks (i.e.,~relation extraction) than language models such as BERT. These knowledge-enhanced language models incorp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ce22345b5d9e173a67328db67550f866
https://doi.org/10.1145/3511808.3557459
https://doi.org/10.1145/3511808.3557459
Autor:
McDonald, Daniel, Jiang, Yueyu, Balaban, Metin, Cantrell, Kalen, Zhu, Qiyun, Gonzalez, Antonio, Morton, James T., Nicolaou, Giorgia, Parks, Donovan H., Karst, Søren M., Albertsen, Mads, Hugenholtz, Philip, DeSantis, Todd, Song, Se Jin, Bartko, Andrew, Havulinna, Aki S., Jousilahti, Pekka, Cheng, Susan, Inouye, Michael, Niiranen, Teemu
Publikováno v:
Nature Biotechnology; May2024, Vol. 42 Issue 5, p813-813, 1p
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.