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pro vyhledávání: '"Kim, Jonggu"'
Autor:
Kim, Jonggu, Lee, Jong-Hyeok
We propose two methods to capture relevant history information in a multi-turn dialogue by modeling inter-speaker relationship for spoken language understanding (SLU). Our methods are tailored for and therefore compatible with XLNet, which is a state
Externí odkaz:
http://arxiv.org/abs/1910.12531
Autor:
Kim, Jonggu, Lee, Jong-Hyeok
To capture salient contextual information for spoken language understanding (SLU) of a dialogue, we propose time-aware models that automatically learn the latent time-decay function of the history without a manual time-decay function. We also propose
Externí odkaz:
http://arxiv.org/abs/1903.08450
Publikováno v:
In Heliyon March 2023 9(3)
Autor:
Shin, Jaegwan, Kwak, Jinwoo, Kim, Sangwon, Son, Changgil, Lee, Yong-Gu, Kim, Jonggu, Bae, Sungjun, Park, Yongeun, Lee, Sang-Ho, Chon, Kangmin
Publikováno v:
In Chemical Engineering Journal 1 January 2023 451 Part 4
Using a sequence-to-sequence framework, many neural conversation models for chit-chat succeed in naturalness of the response. Nevertheless, the neural conversation models tend to give generic responses which are not specific to given messages, and it
Externí odkaz:
http://arxiv.org/abs/1805.08983
Autor:
Kim, Jonggu, Lee, Jong-Hyeok
Most of neural approaches to relation classification have focused on finding short patterns that represent the semantic relation using Convolutional Neural Networks (CNNs) and those approaches have generally achieved better performances than using Re
Externí odkaz:
http://arxiv.org/abs/1707.01265
Publikováno v:
In Computer Speech & Language March 2020 60
Publikováno v:
In The Journal of Urology April 2007 177(4) Supplement:515-515
Publikováno v:
In The Journal of Urology April 2007 177(4) Supplement:35-35
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