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Augmenting pre-trained language models with knowledge graphs (KGs) has achieved success on various commonsense reasoning tasks. However, for a given task instance, the KG, or certain parts of the KG, may not be useful. Although KG-augmented models of
Externí odkaz:
http://arxiv.org/abs/2104.08793
Autor:
Rambhatla S; Computer Science Department, University of Southern California, Los Angeles, CA, U.S.A., Huang S; Keck School of Medicine, University of Southern California, Los Angeles, CA, U.S.A., Trinh L; Computer Science Department, University of Southern California, Los Angeles, CA, U.S.A., Zhang M; Computer Science Department, University of Southern California, Los Angeles, CA, U.S.A., Long B; Computer Science Department, University of Southern California, Los Angeles, CA, U.S.A., Dong M; Computer Science Department, University of Southern California, Los Angeles, CA, U.S.A., Unadkat V; Computer Science Department, University of Southern California, Los Angeles, CA, U.S.A., Yenikomshian HA; Southern California Regional Burn Center at LAC+USC, University of Southern California, Los Angeles, CA., Gillenwater J; Southern California Regional Burn Center at LAC+USC, University of Southern California, Los Angeles, CA., Liu Y; Computer Science Department, University of Southern California, Los Angeles, CA, U.S.A.
Publikováno v:
AMIA ... Annual Symposium proceedings. AMIA Symposium [AMIA Annu Symp Proc] 2022 Feb 21; Vol. 2021, pp. 1039-1048. Date of Electronic Publication: 2022 Feb 21 (Print Publication: 2021).
