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of 21
pro vyhledávání: '"Watanabe, Yotaro"'
Prior work on multilingual sentence embedding has demonstrated that the efficient use of natural language inference (NLI) data to build high-performance models can outperform conventional methods. However, the potential benefits from the recent ``exp
Externí odkaz:
http://arxiv.org/abs/2403.17528
Diffusion generative models have emerged as a new challenger to popular deep neural generative models such as GANs, but have the drawback that they often require a huge number of neural function evaluations (NFEs) during synthesis unless some sophist
Externí odkaz:
http://arxiv.org/abs/2112.13339
This paper is the first attempt to learn the policy of an inquiry dialog system (IDS) by using deep reinforcement learning (DRL). Most IDS frameworks represent dialog states and dialog acts with logical formulae. In order to make learning inquiry dia
Externí odkaz:
http://arxiv.org/abs/1708.00667
Publikováno v:
FedCSIS
Event relation knowledge is important for deep language understanding and inference. Previous work has established automatic acquisition methods of event relations that focus on common sense knowledge acquisition from large-scale unlabeled corpus. Ho
Autor:
Muraoka, Masayasu, Shimaoka, Sonse, Yamamoto, Kazeto, Watanabe, Yotaro, Okazaki, Naoaki, Inui, Kentaro
Publikováno v:
Proceedings of the 28th Pacific Asia Conference on Language, Information and Computation. :65-74
Akademický článek
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Publikováno v:
Computational Linguistics & Intelligent Text Processing (9783642372469); 2013, p545-558, 14p
Publikováno v:
Information Retrieval Technology (9783642353406); 2012, p126-137, 12p
Autor:
Murakami, Koji, Nichols, Eric, Mizuno, Junta, Watanabe, Yotaro, Masuda, Shouko, Goto, Hayato, Ohki, Megumi, Sao, Chitose, Matsuyoshi, Suguru, Inui, Kentaro, Matsumoto, Yuji
Publikováno v:
Proceedings of the Fourth Workshop: Analytics for Noisy Unstructured Text Data; 10/26/2010, p59-66, 8p